Forthcoming and Online First Articles

International Journal of Modelling, Identification and Control

International Journal of Modelling, Identification and Control (IJMIC)

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International Journal of Modelling, Identification and Control (87 papers in press)

Regular Issues

  • Outlier detection algorithm based on deviation characteristic   Order a copy of this article
    by Yong Wang, Hongbin Wang, Pengcheng Sun, Xinliang Yin 
    Abstract: Outlier mining focuses on researching rare events through detection and analysis to dig out the valuable knowledge from them. In the static data set environment, the traditional LOF algorithm calculates the local outlier factor through the whole data set and requires a lot of computing time. To solve this problem, the algorithm divides the data space into grids, and calculates the local outlier factor based on the centroids of the grids. Since the grid number is less than data point number, the time complexity is obviously reduced under acceptable error. When the new data points are added, it can rapidly detect outliers. The contrast experiment results show that the new algorithm can reduce the computation time and improve the efficiency, while achieving comparable accuracy.
    Keywords: outlier detection; local outlier factor; deviation characteristic; fast LOF detection algorithm.

  • Development of control-oriented models for a building under regular heating, ventilation, and air-conditioning operation: a comparative simulation study and an experimental validation   Order a copy of this article
    by Heman Shamachurn, S.Z. Sayed Hassen 
    Abstract: The development of models is a major barrier to the fast and widespread adoption of model predictive control for building HVAC systems. This paper proposes the subspace identification technique, refined through the prediction error method, to quickly obtain a model for the accurate indoor temperature prediction, even with little identification data, even in the presence of large unmeasured disturbances and noisy identification data, and even using data which was collected during the regular HVAC operation of a building. The identification issues associated with grey-box models were thoroughly investigated. In particular, the development of a grey-box model was found to be a complex, lengthy and computationally intensive process, even for a single-zone building, and the models were not physically meaningful. The proposed method was found to be much easier and faster, with a potential for direct practical application. Analysis on experimental data from an existing building provided promising results.
    Keywords: RC model; subspace identification; regular HVAC operation; open-loop data; closed-loop data; experimental validation; DesignBuilder.

  • Volterra series based nonlinear system identification methods and modelling capabilities   Order a copy of this article
    by Gargi Trivedi, Tarun Rawat 
    Abstract: The current study discusses Volterra series based non-linear system models such as Taylor series, Time-delay neural network (TDNN) and Non-linear autoregressive model (NARX). The study aims to construct a truncated second-order Volterra model that can be used to identify non-linear systems and compare its performance to that of a TDNN using benchmark cases. The feasibility of feedback and feedforward networks is evaluated using a dataset of cortical responses evoked by wrist joint manipulation. It is observed that TDNN is a mathematical model with more customizable parameters and require less computation time than Volterra system with particle swarm optimization (PSO). Also, open-loop connections with less a-prior system assumptions, such as Volterra can estimate 42% of wrist dynamics and closed-loop connections like NARX model can estimate 93% of complex non-linear dynamics.
    Keywords: Volterra; TDNN; NARX; model structure.

  • Investigation of transverse vibration suppression of hoisting catenaries in mine hoists by virtual prototype and uniform design   Order a copy of this article
    by Yu Zhu, Tong Xu, Jiannan Yao 
    Abstract: In the hoisting process of an ultra-deep mine shaft, the winding movement of ropes on the Lebus drum will cause transverse vibrations of the catenaries, leading to intense swing of the rope and even winding confusion. In this paper, the transverse vibration virtual model of the catenary was firstly established using bushing sleeve force method in ADAMS, then the displacement response of the catenary under the drum excitation was obtained. Secondly, the correctness of the established model was verified by comparing the numerical simulation results to the ADAMS model results. Finally, a spring-damper device was proposed to further suppress the transverse vibration of the catenary based on the boundary control. The reasonable values of the stiffness and damping parameters of the damper were obtained by applying the uniform experimental design. This study provides a theoretical support for the reduction of the transverse vibration of hoisting catenary.
    Keywords: hoisting catenary; transverse vibration; virtual prototype; spring-damper device; uniform design; vibration suppression.

  • Generating synthetic wind speed scenarios using arti ficial neural networks for probabilistic analysis of hybrid energy systems   Order a copy of this article
    by Jun Chen, Junhui Zhao 
    Abstract: Hybrid energy systems (HES) have been proposed to include and co-optimize multiple energy inputs and multiple energy outputs to enable increasing penetration of clean energy such as wind power. To optimize the system design, extensive data sets of renewable resources for the given location are required, whose availability may be limited. To address this limitation, this paper proposes an innovative methodology to generate synthetic wind speed data. Specifically, artificial neural networks are adopted to characterize historical wind speed data and to generate synthetic scenarios. In addition, Fourier transformation is used to capture the characteristics of the low frequency components in historical data, allowing the synthetic scenarios to preserve seasonal trend. The proposed methodology enables the possibility of Monte Carlo simulation of HES for probabilistic analysis using large volumes of heterogeneous scenarios. Case study of probabilistic analysis is then performed on a particular HES configuration, which includes nuclear power plant, wind farm, battery storage, electric vehicle charging station, and desalination plant. Wind power availability and requirements on component ramping rate are then investigated.
    Keywords: artificial neural networks; Fourier transformation; hybrid energy systems; synthetic scenarios; wind energy.

  • Unknown input observer For linear singular systems with variable delay: the continuous and the discrete time cases   Order a copy of this article
    by Fatma Hamzaoui, Malek Khadhraoui, Hassani Messaoud 
    Abstract: In this paper, we propose a new approach to design a functional observer for linear singular systems with unknown inputs. Variable-Time delay is present in both state and input vectors. The proposed observer is developed in time and frequency domains. The time domain observer design is obtained for both continuous and discrete time systems. The procedure design is based on the unbiasedness of the estimation error dynamic of the observer using Lyapunov functional. The problem is solved by means of Linear Matrix Inequalities to nd the optimal gain implemented in the functional observer design. Frequency domain procedure is derived from time domain results, where we propose a suitable co-prime Matrix Fractions Descriptions. The main interest is that the proposed algorithm estimates both a functional state and the unknown input dependently from the considered delay in time and frequency domains. The proposed observer proves its e ectiveness on a given numerical example.
    Keywords: continuous and discrete time cases; time and frequency domains; unknown additional inputs; functional observers; variable delay; MFD; LMI.

  • Adaptive PID computed-torque control of robot manipulators based on DDPG reinforcement learning   Order a copy of this article
    by Akram Ghediri, Kheireddine Lamamra, Abdelaziz Ait Kaki, Sundarapandian Vaidyanathan 
    Abstract: This paper presents a design of an adaptive PID gain tuning based on Deep Deterministic Policy Gradient reinforcement learning agent for PID Computed-torque control of robot manipulators, taking the presence of unmodeled dynamics and external disturbances into consideration. The proposed approach adaptively computes the outer-loop PID controller gains, that minimize trajectory tracking errors and reject disturbances, with the closed-loop dynamics remain stable. Since the control scheme requires the knowledge of the robots dynamics, both kinematic and dynamic equations of n-link serial manipulator are developed. The agent is implemented on UR5e robot manipulator model, using the most valid dynamic and kinematic parameters provided by the manufacturer and related works. Simulation results show that the proposed approach is robust against bounded internal and external disturbances, and achieves a good trajectory tracking performance, due to the adaptability of gain tuning over the conventional PID controller.
    Keywords: UR5e robot manipulator; adaptive PID control; computed-torque control; DDPG reinforcement learning; trajectory tracking; disturbance rejection.

  • Advanced genetic algorithm based PID controller for air levitation system   Order a copy of this article
    by D.P. Gaikwad, B. Patil, L. Patil 
    Abstract: In industrial control systems, PID controllers are being widely used due its simple working principles. Many control and instruments engineers and operators use PID controllers in daily life. PID controllers allows for many variations which can cope with a wide range of systems and conditions. For increasing performances of PID controller, fine tuning of its parameters are required. Many authors have used different optimization algorithms to tune parameters of PID controllers. These optimization algorithms offer less performance. In this paper, the fine-tuned PID controller is proposed for the air levitation system. Advanced genetic algorithm is used for tuning parameters of PID controllers. For demonstration of efficiency and applicability of the proposed PID controller, simulation based experimentations have conducted. The proposed PID design method has linked with other three optimization techniques. Ant colony optimisation, particle swarm optimisation and fuzzy logic are used for performance comparison of advanced genetic algorithm based PID controllers. In experimental results, we have got very small values of IAE, ISE and ITAE using the proposed method. It indicates that the proposed PID design method offers improved performance over the other three optimisation based PID design methods and other existing methods.
    Keywords: PID; integrating; process model; tuning; stability.
    DOI: 10.1504/IJMIC.2022.10047441
  • An enhancement in parallel cascade scheme for non-minimum phase system   Order a copy of this article
    by Manish Yadav, Hirenkumar Patel 
    Abstract: This paper aims to control non-minimum phase (NMP) systems with dead time in the existence of uncertainty and disturbances. The parallel cascade control is utilized to motivate such problems, especially for slow process dynamics and actuator nonlinearities. The novelty lies in this work, combination of a higher-order fractional-filter with an inverse response and dead-time compensator in the Internal Model Control (IMC) framework for designing the outer loop controller. The inner loop controller assumes the standard IMC controller. This modified structure is offered refinement in the gain margin for better robustness. The Riemann sheet principal is used to stability investigation of factional quasi characteristic polynomial arises from the non-minimum phase systems with dead time. Further, a robustness test is also carried out via sensitivity analysis. The efficacy of the suggested method is illustrated via two case studies.
    Keywords: non-minimum phase; parallel cascade control; IMC controller; robustness.

  • Kharitonov polynomial based interval reduced order modelling of Cuk Converter   Order a copy of this article
    by V.P. Meena, V.P. Singh 
    Abstract: This paper proposes method of reduced order modelling for the Cuk converter using a state-space-averaging (SSA) technique, in which combined state-space description is obtained and output to control for the Cuk converter transfer function is determined. However, there may be some variation in parameters of system owing to uncertainties and imperfect modelling that are addressed using interval modelling. Thus, the obtained interval model is reduced further using Kharitonov polynomials. Routh-Pad
    Keywords: Cuk converter; interval modelling; interval systems; Kharitonov polynomials; order reduction; parametric uncertainty; state-space averaging.

  • A TCPN-based model for testing distributed systems with timing constraints   Order a copy of this article
    by Salma Azzouzi, My El Hassan Charaf 
    Abstract: This paper focuses on extending the basis of distributed testing to address the testing process for time-sensitive distributed systems. In this context, we present an alternative approach to manage the problems that occur in this area, commonly referred to as controllability, observability and synchronisation issues. The key point of the proposed study is to define the activities of each tester through a set of timed distributed testing rules. Thus, we present our algorithm for the generation of such rules. Each rule is handled as a data structure comprising the data to be sent or received, the guard to be controlled and the set of clocks to be updated at the end of each transition. Afterwards, we show how we can use a timed coloured Petri nets model to cope with the complex tasks of the monitoring of testers in the distributed test context. The simulation results revealed the effectiveness of our approach in providing correct execution of the system actions and also show how the response time of each tester can be improved by considering the temporal constraints. Indeed, the test becomes non-blocking and stops immediately by returning a false verdict if the temporal constraints have not been met.
    Keywords: distributed testing; controllability; observability; synchronisation; timed coloured Petri net.

  • A fixed wing UAV with VTOL capabilities: design, control and energy management   Order a copy of this article
    by Luca Pugi, Alberto Mela, Alberto Reatti, Armando Casazza, Roberto Fiorenzani, Giuseppe Mattei 
    Abstract: There is an increasing interest for UAVs (Unmanned Aerial Vehicles) with mixed, multi-rotor propulsion layouts able to assure desirable feature of both fixed wing systems (efficiency high cruising speed autonomy) and capabilities of rotating wing ones (hovering, vertical take off and landing capabilities). This work investigated a mixed propulsion layout with five electric propellers fed by an hybrid energy management system able to assure an higher autonomy respect to a pure electric solution. The proposed system is investigated through the development of a model able properly to simulate complex interactions arising between different propulsion, control and energy management subsystems. In this way, it was possible to propose and calibrate an efficient energy management policy and to evaluate how different transition policies between hovering and fixed wing cruising should affect involved energy consumptions. Finally, the proposed model was used to simulate a complex mission profile in order to both verify manoeuvring capabilities of the system and predict energy consumption. At the end it was possible to verify not only the feasibility of the proposed solution with respect to the completion of a complex mission profiles but also the potentialities and utility of the adopted simulation models.
    Keywords: mechatronics; UAV; VTOL; hybrid propulsion.

  • Orientation effect on the stability conditions of fronts in a liquid and porous medium   Order a copy of this article
    by Hamza Rouah, Ahmed Taik 
    Abstract: In this article, we have studied the influence of orientation on the conditions of stability of the reaction fronts in two cases: the first case where the liquid monomer is converted into solid polymer in a liquid medium and the second case where the monomer and the polymer are liquid in a porous medium. Zeldovich and Frank-Kamenetskii method are used to perform the asymptotic analysis taking the inverse of Zeldovich number as a critical parameter. The linear stability analysis is fulfilled to investigate the resulting interface models for both cases. The dispersion relation obtained for both cases is solved numerically and then the conditions for cellular and oscillatory instability are determined. We showed that the angle of inclination affects the conditions of thermal and convective instability in a liquid and porous medium.
    Keywords: frontal polymerisation; reaction-diffusion equations; reaction fronts; stability analysis.

  • Power quality assessment and power quality improvement in a hospital facility   Order a copy of this article
    by Sachin R, Nagesh H B 
    Abstract: The power quality (PQ) assessment is carried out at a KIMS hospital facility by conducting the harmonic study as per IEEE3002.8 guidelines. As per PQ data obtained, the hospital facility is experiencing a significant number of PQ disturbances and violating IEEE519 limits for PQ in special application systems. It is found necessary to use a compensator for PQ improvement. A cost-effective compensator dynamic voltage restorer (DVR) is designed to improve the PQ in the hospital facility. The designed DVR controller model is tested in the RT-LAB hardware-in-loop real-time simulation platform using OPAL-RT with multicore FPGA processors to validate the compatibility of the designed controller to be applied for real system implementation. Thus, PQ assessment helps in the appropriate design of compensating controllers to suit practicality. A comparative study of the choice of designed DVR controllers, such as PI, Fuzzy, ANN, ANFIS-PI optimized and ANFIS-Fuzzy optimised controllers tested in real-time for different cases and for different loading conditions is summarised.
    Keywords: adaptive neuro fuzzy inference system; artificial neural network; dynamic voltage restorer; fuzzy logic controller; proportional integral controller; power quality.
    DOI: 10.1504/IJMIC.2022.10049013
  • Identification of the most conservative stability bounds for a class of multi-rate haptics controllers   Order a copy of this article
    by Suhail Ganiny, Majid H. Koul, Babar Ahmad 
    Abstract: This work identifies the most conservative stability bounds applicable to a class of multi-rate haptic controllers that involve sampling of a single state variable at two distinct rates for rendering a virtual wall. In particular, the uncoupled stability boundaries of a dual-rate haptic controller have been determined. In contrast to the prior research, the current work extends the scope in terms of identification of the impedance parameters that establish the worst-case stability limits that are closest to the experimental results. Our analysis reveals that the transformation sequence ZOH-Tustin-ZOH yields the most conservative, while the half-sample delay approximation approach yields the least conservative estimates of the stability bounds. Specifically, the relative root-mean-square error (RRMSE) between the experimental outcomes and the results predicted by the ZOH-Tustin-ZOH transformations varies between 0.54-0.83, while for the half-sample delay approximation it varies from 1.21-3.2.
    Keywords: multi-rate controller; impedance haptic interfaces; stability bounds.

  • Gear faults identification based on big data analysis and Catboost model   Order a copy of this article
    by Yongsheng Qi, Xiaoda Zhang, Jianxin Zhang 
    Abstract: The gear faults identification based on big data analysis and Catboost is investigated. The big data sets with nine and ten features for five gear faults are constructed, respectively. The Catboost model based on the above two data sets is constructed and trained. The testing results show that Catboost, XGBoost, and LGBM models based on the data set with ten features are better than ones with nine features, and the fault identification accuracy and time obtained by Catboost are better than the other two models. By calculating the influence of features to the identification results, it can be found that four features play the crucial roles. The Catboost based on the data set with the above four characteristics and five faults is verified to achieve identification accuracies and times of are 100% and 680 s, respectively, which are better than ones obtained by using XGBoost and LGBM.
    Keywords: gear faults identification; big data analysis; Catboost; classification prediction; feature importance.

  • Displacement tracking of uncertain nonlinear cardiovascular muscle using Lyapunov function with disturbance observer-based control   Order a copy of this article
    by Soumyendu Bhattacharjee, Sourish Sanyal, Madhabi Ganguly, Aishwarya Banerjee, Biswarup Neogi 
    Abstract: The nature of cardiovascular muscle was modelled primarily using some very basic mechanical elements, among which some were considered as a linear element so that the design can be easily understood. Owing to non-zero reaction time of cardiovascular muscle, the overall model becomes nonlinear. Nonlinear behaviour of the proposed model has been explained using some very common types of nonlinearity, such as dead-zone and saturation. Robust control of uncertain nonlinear human cardiovascular muscle dynamics is investigated using Lyapunov stability theory along with an observer-based control system. In this work, a nonlinear controller has been designed in the absence of uncertainty and any other disturbances to track the displacement of muscle dynamics. To achieve good tracking performances, stability analysis of the plant-sensor system has successfully been done in more than one time considering different situations. Finally, an asymptotical stability has been found towards the proposed nonlinear system.
    Keywords: DOBC approach; Lyapunov stability; non-linearity; robust control design; uncertainity.

  • An adaptive disturbance multi-objective evolutionary algorithm based on decomposition   Order a copy of this article
    by Yanfang Shi, Jianguo Shi 
    Abstract: In solving multi-objective optimisation problems, the uniformly distributed weight vector of decomposition based multi-objective evolutionary algorithm (MOEA/D) is not completely suitable for the non-uniformly distributed Pareto front (PF). In order to solve the situation above, this paper proposes an Adaptive Disturbance Multi-Objective Evolutionary Algorithm based on Decomposition (AD-MOEA/D), the proposed algorithm introduces the disturbance individuals and disturbance weight vectors during the evolution. The disturbance individuals maintain the population diversity and improve convergence accuracy. The disturbance weight vectors assist the weight vectors to adjust adaptively and improve the distribution of PF. Besides, both disturbance individuals and disturbance weight vectors are produced according to the actual evolution, which will not participate in evolution when it is not necessary. The experimental results on multi-objective test functions show that the PF optimised by AD-MOEA/D has better convergence and distribution.
    Keywords: multi-objective evolutionary algorithm; disturbance individuals; disturbance weight vectors; decomposition.

  • Strong Wolfe condition based variable stacking length multi-gradient parameter identification algorithm   Order a copy of this article
    by Yiqiao Shi, Shaoxue Jing 
    Abstract: This paper considers the acceleration of the gradient algorithm for the linear models. The traditional stochastic gradient algorithm requires less computation, but it converges to the true parameter slowly. To accelerate the gradient algorithm, a novel gradient algorithm using several gradients is proposed. One important issue of the proposed algorithm is how to determine the stacking length. The stacking length defines the number of gradients used in each recursion. A variable stacking length based on the strong Wolfe condition is presented to enable the algorithm to converge faster. The stacking length obtained by using the strong Wolfe condition can ensure that the proposed multi-gradient algorithm converges faster. Several experiments are made to validate the proposed algorithm.
    Keywords: parameter estimation; stochastic gradient; multi-gradient; strong Wolfe condition; convergence speed.

  • Four generations of control theory development   Order a copy of this article
    by T.C. Yang 
    Abstract: In our control community, in particular in our teaching, we often use the terms classical control theory and modern control theory. History moves forward. The word modern here is not appropriate. Todays modern is futures classical. Nevertheless, behind the ambiguous words they are meaningful terms: transfer function based for classical control, and state-space based for modern control. Looking back and forward, and to give an overall overview, this short article presents an opinion that control system study up to date can be divided into four generations; namely, 1) transfer function based; 2) state-space based; 3) networked control systems; and 4) control in the new AI era.
    Keywords: control theory development; four generations; control in the new AI era.

  • 3D indoor reconstruction using Kinect sensor with locality constraint   Order a copy of this article
    by Peng Zhu, YanGuang Guo 
    Abstract: In this paper, an indoor 3D construction is proposed based on RGB-D measurement. It is intentionally designed to solve the traditional issues, such as cloud registration inaccuracy, large computational time. Firstly, potential candidates are extracted by Harris detector, and the SURF method is used to generate the feature descriptors. Afterwards, the correct functional match is selected by RGB and depth measurements with neighbouring constraint. Lastly, 3D clouds are formed through graphical optimization. In the experiment, the RGB-D sensor is rigidly fixed on the mobile platform to reconstruct the indoor 3D scene, which shows comparable performance in terms of computational time and accuracy.
    Keywords: RGB-D; 3D indoor reconstruction; Kinect; point cloud; SURF method.

  • HMM-based IMU data processing for arm gesture classification and motion tracking   Order a copy of this article
    by Danping Wang, Jina Wang, Yang Liu, Xianming Meng 
    Abstract: This paper investigates Inertial Measurement Unit (IMU) data processing methods for human gesture classification and arm motion tracking in Wireless Body Sensor Network (WBSN). The method is adopted that consists of two main stages. In the training stage, the supervised learning method is adopted to obtain the HMM model and the Viterbi algorithm is used to obtain the optimal hidden state sequence in the testing stage. HMM also complements the intuitional evaluation for arm motion recovery. We take advantage of the twists and exponential maps to recover the arm motion process. In addition, visual tracking device-VICON is used to validate the accuracy of the inertial tracking system. The experimental results show that the HMM algorithm gesture classifier achieves up to 96.63% accuracy on five commonly used arm gestures and visual assisted tracking outcomes verify the robustness and feasibility of the IMU tracking device.
    Keywords: gesture classification; arm motion tracking; inertial measurement unit; computer network; vision motion tracking.

  • A novel adaptive variable speed control strategy for wound rotor induction motors   Order a copy of this article
    by Dieudonné Ekang, Donatien Nganga-Kouya, Aime Francis Okou 
    Abstract: A new approach is proposed for the design of an adaptive variable speed control for an induction motor. This design approach is based on a new model for induction motors in the (/) reference frame. The model state variables are constant in steady state and therefore enable the application of adaptive backstepping control design techniques to find controller equations and adaptation laws that insure that the rotor speed and flux track their reference values despite signification changes in machine resistances and inductances due to temperature and magnetic saturation. The proposed controller is tested in simulation. Results show robust steady state and transient performances.
    Keywords: wound rotor of induction motor; adaptive backstepping control; speed control; rotor flux control; stability analysis.

  • Experimental parameter estimation methodology based on equivalent output injection   Order a copy of this article
    by David Rosas, Karla Espinoza, Karla Velazquez 
    Abstract: This work proposes a methodology to estimate parameters for linear and nonlinear dynamical systems, with partial state measurement, that satisfy the property of parameter linearity. This methodology is experimental, off-line, and recursive. It uses discontinuous state observers to estimate all state variables and the disturbance terms needed in the estimation processes. Because the equivalent output injection corresponds to the disturbances produced by the parameter uncertainties, the methodology allows us to obtain the best parameter estimation by minimizing an index related to the power of the equivalent output injection; a smaller value represents a better estimation. With this parameter estimation, we can establish a model that facilitates the design and implementation of many control algorithms, including robust controllers. We validate the methodology through numerical simulations and experiments with linear, nonlinear, and discontinuous systems. Based on the experimental results, we conclude that the proposed algorithm's performance is better than other methodologies.
    Keywords: identification; modelling; equivalent output injection; discontinuous observers; least squares algorithm.
    DOI: 10.1504/IJMIC.2022.10050341
  • A continuous-time fault-tolerant predictive control approach for wind turbines   Order a copy of this article
    by Rime Elhouti, Selma Sefriti, Ismail Boumhidi 
    Abstract: This paper present a developed fault-tolerant control technique for the wind turbine system. The proposed approach is a combination of an additive sliding mode with a predictive model based controller. The online continuous-time model predictive controller (CMPC) is designed to be a nominal controller for maximum power tracking and tolerates the actuator loss of faults, while the additive term is responsible for ensuring more robustness with respect to the various actuator faults. The considered controller uses the full state of the system, so, a robust observer is proposed for estimating the full state needed in the control law. The obtained results in the simulation part show the efficiency of the proposed method for both maximum power tracking and handling the system actuator faults.
    Keywords: predictive control; fault-tolerant control; sliding mode observer; wind turbine.

  • Parameter identification for a model of gas exchange dynamics during cycling   Order a copy of this article
    by Nadia Rosero, Maxime Chorin, John Jairo Martinez Molina 
    Abstract: This paper presents the modelling and parameter identification of the gas exchange dynamics during cycling. A discrete-time linear parameter-varying model is proposed, which relates the dynamics of oxygen consumption and carbon dioxide production with the developed pedal power. A state-dependent non-linear function is used for modelling the excess carbon dioxide production. The approach proposed for parameter identification is based on specific exercise scenarios tailored to the considered individual, which narrows the data acquisition process. The parameter identification process is performed as a solution of a sequence of non-linear unconstrained optimization problems using measured data from different cycling scenarios. An illustration of the methodology used for the identification and the validation of the model is also presented.
    Keywords: model identification; gas exchange; cycling; model checking; physiology.

  • Optimal control strategies-based maximum power point tracking for photovoltaic systems under variable environmental conditions   Order a copy of this article
    by Sally Abdulaziz, Galal Attlam, Gomaa Zaki, Essam Nabil 
    Abstract: To increase the efficiency of photovoltaic (PV) array output under variable environmental conditions, maximum power point tracking (MPPT) of the solar arrays is needed. This paper proposes Fuzzy Logic Controller (FLC) based MPPT, Artificial Neural Network (ANN) based MPPT, Neuro-Fuzzy (NF) based MPPT, Particle Swarm Optimisation (PSO) based MPPT, and Cuckoo Search (CS) algorithm based MPPT to combine an adaptive controller and an optimisation, to guarantee global stability and a constant settling time for all operation conditions. This combination enables an increase in the power generated in comparison with conventional MPPT techniques. Simulation results show that the proposed photovoltaic/storage generator is able to supply the suggested dynamic loads under different conditions, and achieve good performance. It is also noticed that operating the photovoltaic array based on maximum power point tracking conditions gives about 43% extra power generation than in the case of normal operation.
    Keywords: DC_DC power converters; fuzzy control; fuzzy neural controller; maximum power point trackers; photovoltaic systems; particle swarm optimisation; renewable energy sources.

  • Impulse-based controller synthesis for a class of polynomial systems   Order a copy of this article
    by Qian Ye 
    Abstract: This paper develops a time-triggered impulsive control strategy for stabilisation problem of a class of polynomial systems. The proposed hybrid control method combines time-triggered impulsive control and state-feedback control. To obtain the control feedback gain, the matrix sum-of-squares programming is employed to solve the feasible solutions of constructed positive polynomial problems. Compared with a single time-triggered impulsive control or the pure state-feedback control, the proposed control method can effectively combine the advantages of the two control methods. In particular, the design of the controller is more flexible and the control effect is greatly improved. Finally, two simulation examples including the Chua's chaotic system are provided to illustrate the effectiveness and superiority of the proposed method.
    Keywords: polynomial system; impulse-based control; state-feedback control; sum-of-squares programming.
    DOI: 10.1504/IJMIC.2022.10051674
  • Boundary control of a flexible beam with output constraint under saturation input   Order a copy of this article
    by Chuyang Yu, Haojie Lin, Xuyang Lou, Jiajia Jia 
    Abstract: This paper focuses on the problem of saturated boundary control for a flexible beam system with unknown disturbances and output constraint. It is aimed to suppress the vibration of the flexible beam system with unknown disturbances and input saturation, and make the pitch of the boundary output remain in the constraint. In order to satisfy the system constraint, an auxiliary term is established and a barrier Lyapunov function is applied. Two boundary controllers with a barrier term and an auxiliary term are constructed to prove the uniform ultimate boundedness of the state of the flexible beam. Numerical simulations are given to verify the effectiveness of the proposed control methods.
    Keywords: flexible beam system; input saturation; output constraint; boundary control; unknown disturbance.

  • Guidelines for choosing hyperparameters of echo state networks for system identification: Two case studies   Order a copy of this article
    by Thiago Ushikoshi, Luis Aguirre 
    Abstract: Echo state networks (ESN) can be used to model dynamical systems in the context of reservoir computing using standard regression algorithms, which is one of its main advantages. However, there are some hyperparameters that need to be carefully chosen and there is no general recommendation on how to perform this important step. After setting the ESN paradigm for system identification, this paper describes the choice of hyperparameters in the context of two case studies: one using experimental data of a pilot heater and the other using the Duffing-Ueda oscillator with chaotic dynamics. The main findings are: (i) ESNs can reproduce the chaotic regime of the Duffing-Ueda oscillator for a specific region on the hyperparameter space, (ii) some hyperparameters may not be critical from a statistical perspective but can still drastically affect the dynamical regime, and (iii) the ESN initialization is not critical when the hyperparameters are adequately chosen.
    Keywords: reservoir computing; echo state networks; ESN; guidelines for echo state networks; hyperparameters of echo state networks; nonlinear models; system identification; dynamical system identification; modelling; chaotic oscillators.

  • Joint variable and variable projection algorithms for separable nonlinear models using Aitken acceleration technique   Order a copy of this article
    by Lianyuan Cheng, Jing Chen, Yingjiao Rong 
    Abstract: This paper proposes a joint variable based gradient descent algorithm (Joint-GD) and a variable projection (VP) based gradient descent algorithm (VP-GD) for separable nonlinear models. The VP algorithm takes advantage of the separability property of variables to reduce the dimensionality of the parameters, which makes the convergence rates faster. In order to speed up the convergence of the gradient descent algorithm, the Aitken acceleration technique is introduced in the algorithms, which is second-order convergent. Moreover, the Aitken based methods are robust to the step-size, therefore they can be widely used in engineering practices. The numerical simulation shows the effectiveness of the proposed algorithms.
    Keywords: variable projection algorithm; joint variable algorithm; gradient descent algorithm; separable nonlinear model; Aitken acceleration technique.

  • Nonlinear system identification using butterfly optimisation algorithm and Hammerstein model   Order a copy of this article
    by Sandeep Singh, Tarun Kumar Rawat, Alaknanda Ashok 
    Abstract: This paper focuses on the nonlinear system identification using butterfly optimisation algorithm (BOA) optimised with adaptive Hammerstein model which is the cascade of nonlinear second-order Volterra (SOV) and linear finite impulse response (FIR) systems. Generally, gradient-based methods have been applied for solving such problems. However, these methods may face the problem of getting trapped in local minimum solution. In this paper, a novel butterfly optimisation algorithm is used to identify the nonlinear system by using three different models namely, Hammerstein model, memoryless polynomial nonlinear (MPN)-FIR and SOV models. Furthermore, to measure the accuracy of the employed BOA, mean square error, coefficient estimation and convergence speed are considered. To prove the efficacy of the proposed BOA, the simulated results has been compared with that of the antlion optimisation algorithm and dragonfly algorithm. The simulated results confirm that Hammerstein model with SOV-FIR optimised with BOA is able to outperform the other models and algorithms.
    Keywords: nonlinear system identification; Hammerstein model; meta-heuristic algorithms; butterfly optimisation algorithm; antlion optimisation algorithm; dragonfly algorithm.
    DOI: 10.1504/IJMIC.2022.10051352
  • Stochastic pointwise second-order maximum principle for optimal continuous-singular control using variational approach.   Order a copy of this article
    by Nour El Houda Abada, Mokhtar Hafayed 
    Abstract: In this paper, we establish a second-order necessary conditions for optimal continuous-singular stochastic control, where the systems is governed by nonlinear controlled It
    Keywords: optimal control; stochastic continuous-singular control; pointwise second-order necessary conditions; variational method.

  • New decentralized control based on T-S fuzzy logic approach of an electrical wind-source integrating grid   Order a copy of this article
    by Mohsen Ben Ammar, Wissem Bahloul, Mohamed Ali Zdiri, Hsan Hadj Abdallah 
    Abstract: The present work is designed to advance a new methodology that allows the implementation of a decentralized control system within a multi-machine grid. The design consists in determining the grid Thevenin equivalent, as conceived by each generator node. Such a process should help in transforming the grid into n machines, whereby, each single machine must be connected to an Infinite Bus (SMIB). Relying on a Blondel diagram, we have been able to define a complete model relevant to each of the grid-associated machines. Given the system non-linearity, application of a Takagi-Sugeno (T-S) fuzzy logic turns out to yield satisfactory results. Noteworthy, is that the investigated test grid has been equipped with a wind turbine, while the considered disturbances are power injected variations by this renewable source. The simulation results, was implemented on the 9-node Western System Coordinating Council (WSCC) grid test, proved the remarkable robustness of the applied control in terms of disturbance reduction.
    Keywords: electrical grid; wind energy; AVR and PSS controllers; Thevenin model; decentralised control; fuzzy logic; electrical machine; WSCC 9 nodes.

  • Identification of the three-axis pedestal using Euler-Lagrange method using mathematical approach   Order a copy of this article
    by S.Mohammadreza Ebrahimi, Behrooz Rezaei, Mehdi Tavan 
    Abstract: Pedestals are considered as an applicable tool to hold and rotate various instruments. One of their important applications is carrying and rotating antenna to precisely track satellites in space so that it can be possible to receive signals sent from the satellites and send information to the satellites as well. The quality of received and sent signals depends on different factors among which selecting an appropriate pedestal and a robust controller play a vital role. Selecting an inappropriate pedestal can lead to losing a part of the information in keyhole of the pedestal. Also, choosing an unsuitable controller causes the pedestal cannot track the satellites precisely or conserve the stability of the nonlinear pedestal system, which results in decreasing performance of the pedestal. Three-axis pedestal is one of the best pedestals ever constructed and can be used in diverse fields due to not having any keyhole. However, it has not been proposed an accurate model for it until now. In this article, an accurate model of the three-axis pedestal system has been extracted. For extracting motion equations of the pedestal in which the Euler-Lagrange method has been used, both rotational movement and transitional movement have been considered to obtain a precise and comprehensive model of the system. Because of the inaccessibility of the actual model and also saving time and cost, the proposed model has been compared with the model simulated in SolidWorks and MATLAB software to carry out validation. The results of simulation and experiments have shown the validity of the modelling.
    Keywords: mathematical model; mobile antenna; XYZ pedestal; modeling; validation; simulation;.

  • Sliding mode switched tracking control of space robot manipulator   Order a copy of this article
    by Juan Wang, Quanze Zhao, Liangliang Sun 
    Abstract: This paper investigates the tracking control of space robot manipulator by sliding mode switched method. According to the difference between space gravity environment and ground gravity environment, a sliding mode switching control strategy based on dwell time was proposed. Since the gravity environment of space robot manipulator is different, the space robot manipulator is modelled as a multi-mode switching system. It is divided into ground subsystem and space subsystem, and different sliding mode controllers are designed respectively. The stability of the switching system is proved by multiple Lyapunov function method and the trajectory track problem of space robot manipulator is realised in the framework of switching control. Finally, the simulation example shows the effectiveness of the proposed control method and the comparative simulation demonstrates the superiority of the proposed control method.
    Keywords: space robot manipulator; switching control; sliding mode control; dwell time.

  • Identification of Hammerstein-Wiener time delay model based on approximate least absolute deviation   Order a copy of this article
    by Baochang Xu, Zhichao Rong, Yaxin Wang, Likun Yuan 
    Abstract: Nonlinearity, time delay and spike noises widely exist in industrial processes. Compared with the linear model, the typical nonlinear Hammerstein-Wiener (H-W) model can describe nonlinear characteristic of industry processes more accurately. In order to overcome the effect of spike noise on the identification results, we propose a stochastic gradient algorithm based on the least absolute deviation in this paper. To solve the non-differentiable problem of the least absolute deviation, an approximate least absolute deviation objective function is established by introducing a deterministic differentiable function to replace the absolute residual. Experiments show the proposed algorithm can suppress the influence of the spike noise on the identification results, and has high identification accuracy and strong robustness.
    Keywords: Hammerstein-Wiener model; approximate least absolute deviation; stochastic gradient; spike noise; time delay.

  • Design of a PEM fuel cell powered autonomous quadcopter   Order a copy of this article
    by Soham Prajapati, S. Charulatha 
    Abstract: The purpose of this paper is to design a PID controller for a detailed nonlinear model of a custom-made quadcopter and utilize the power requirements in designing a proton exchange membrane (PEM) fuel cell system. The first principles methodology to commence with unmanned aerial vehicle architecture is delineated. The empirical actuator response of the brushless DC (BLDC) which further adds accuracy to the mathematical model of the system. The paper also presents simulations for nonlinear open loop and closed loop feedback with PID controller. The controller gains are obtained from the simulations for hover flight mode. The experimental implementation of battery powered quadcopter is validated with simulation results of PID control design. Finally, a mathematical model of a PEM fuel cell system for proposed quadcopter model is presented. The key limitation of this paper is the absence of experimental data for fuel cell model due their high cost and low-availability.
    Keywords: drone CAD model; quadcopter dynamics; PID control; fitting thrust vs RPM curves; hover flight mode; PEM fuel cells; hydrogen powered; zero-emission technology.

  • Force/Position Control of Constrained Reconfigurable Manipulators with Sliding Mode Control based on Adaptive Neural Network   Order a copy of this article
    by Ruchika , Naveen Kumar 
    Abstract: A reconfigurable manipulator can achieve proficient end effector and elongate workspace. However, deformable link causes frequent changes in shape and therefore brings difficulties to model and control the manipulator. In view of distinctive behaviour because of bending operation, a sliding mode based mechanism with no prior dynamic information is introduced for validated control operation. The nonlinear terms are included in the sliding mode to improve the convergence rate. Moreover, we show that fast terminal sliders reinforce parametric uncertainty as compared to conventional sliders. The neural network system is adopted for the estimation of nonlinear components whereas the friction term and constraint force of each joint are compensated with the help of adaptive control. The Lyapunov theory proves the stability of a closed-loop system. Finally, simulations are performed in a comparative manner with two different configuration controls that will provide the benefit of the design method.
    Keywords: finite time convergence; RBF neural network; adaptive bound; reconstruction error; terminal sliding mode control.

  • Universal activation function for data-driven gait model   Order a copy of this article
    by Bharat Singh, Suchit Patel, Ankit Vijayvargiya, Rajesh Kumar 
    Abstract: Gait generation for the biped robot is a very tedious task owing to higher degrees of freedom and an uncertain environment. Deep learning approaches can be employed for the modelling of real human kinematics, which can be further applied as a reference to the biped robot. However, choosing the right activation function is a very challenging task. This research work proposed the universal activation function for the kinematic modelling which is adaptive in sense of application. Twenty-five different activation function from the literature is compared with the presented activation function in term of mean and maximum model prediction error along the gait trajectory. It shows that the universal activation function-based gait model outperforms others by large margins. Additionally, the parameter sensitivity of the presented activation function is discussed in detail. Furthermore, two cases of 5% and 10% variation in the input are analysed to evaluate the prediction ability of the developed gait model with a 95% prediction interval.
    Keywords: gait model; activation function; prediction interval; data-driven; biped robot.

  • Extended linear quadratic regulator control and its application in trajectory following control of autonomous vehicles   Order a copy of this article
    by Jianwei Wu, Lin Chen, Yang Zhou, Beibei Sun 
    Abstract: Owing to the limitation that the linear quadratic regulator (LQR) method cannot consider the weight of input rate, we propose an extended linear quadratic regulator (ELQR) method, and further extend the application of the LQR. Considering that the standard Riccati equation cannot be obtained after adding the weight term of input rate in the quadratic performance index, it cannot be solved by the traditional matrix algebra equation method. Therefore, an optimisation model is constructed, and is solved by the genetic algorithm. A simulation example from the trajectory following control for autonomous vehicles, which need to consider the limitations on the angular velocity of front steering to ensure safe driving, is given to illustrate the effectiveness of the ELQR in this paper. The results show that both the LQR and ELQR can achieve the expected control effects. Compared with the LQR, the ELQR considering the weight of input rate has obvious advantages, which avoids exceeding the limitations on the angular velocity of front steering and thus improves safety and comfort of driving.
    Keywords: ELQR; LQR; weight of input rate; genetic algorithm; algebraic Riccati equation.

  • Equal-weight and rank-sum-weight based systematic diminution of higher order continuous systems using grey wolf optimisation   Order a copy of this article
    by Umesh Kumar Yadav, Naresh Patnana, V.P. Meena, V.P. Singh 
    Abstract: The order-diminution techniques are adopted in various fields of engineering and applications to reduce the order of systems from higher order to desired lower order. In this research proposal, diminution of higher-order continuous systems (HOCSs) is done by incorporating systematic procedures for determination of weights. The errors between time-moments and Markov parameters of HOCS and desired reduced-order model (ROM) are used to frame the objective function. In the objective function, associated weights are determined using systematic procedures. The systematic procedures exploited in this work are equal-weight method and rank-sum-weight method. The minimisation of the framed objective function is done using the grey wolf optimisation algorithm. The effectiveness and superiority of proposed method is claimed with the help of tenth-order and seventh-order systems by considering them as test cases. The comparative analysis is done by tabulating the time-domain specifications and error-indices. The responses of the HOCS and ROMs are also presented, to prove the efficacy and effectiveness of the proposed method.
    Keywords: higher-order continuous systems; grey wolf optimisation algorithm; order-diminution; reduced-order model; systematic procedures.

  • A collaborative channel gain and delay estimation algorithm based on dynamic state space model   Order a copy of this article
    by Danping Wang, Yang Liu, Yanhui Wang 
    Abstract: In order to overcome the serious impact of the presence of fading and sensing delay factors in the channel on the performance of spectrum sensing, a novel joint channel gain and sensing delay algorithm is proposed in this paper. A dynamic state space model is constructed to establish the relationship between the PU state, the dynamic fading channel state and the perceived delay. The channel gain can be obtained by means of hidden Markov chain and maximum a posteriori probability. Moreover, the perceived delay value can be obtained by random walk model and sequential particle filtering method. The performance evaluation performed by simulation shows that the algorithm is able to eliminate the uncertainty information in the signal, and the spectrum sensing performance and the sensing delay are significantly improved.
    Keywords: spectrum sensing; joint estimation; perceptual delay; channel gain.

  • Anti-local occlusion intelligent classification method based on Mobilenet for hazardous waste   Order a copy of this article
    by Jinxiang Chen, Yiqun Cheng, Jianxin Zhang 
    Abstract: Anti-local occlusion intelligent classification methods based on Mobilenet and VTM for hazardous waste are investigated in this paper. Three image data sets with ten kinds of hazardous waste and 5000 samples are constructed, which include the image data set with without occlusion, the image data set with 15% occlusion, and the image data set with random occlusion. Based on them, the Mobilenet and VTM intelligent classification model are constructed, trained, and tested. It can be seen from the testing results that the classification accuracies of VTM and Mobilenet are very high for the image data set with and without occlusion. But as occlusion areas on images go up or randomly change, the classification accuracies of VTM and Mobilenet go down for 15% and random occlusion cases. The testing results show that classification accuracy of Mobilenet model is better than that of VTM model for hazardous waste with or without occlusion.
    Keywords: hazardous waste classification; occluded target identification; VTM; Mobilenet.

  • Surface detection method of glass fibre composites based on computer vision   Order a copy of this article
    by Yanfang Shi, Jianguo Shi 
    Abstract: Considering the high cost, low efficiency and poor real-time performance of manual inspection methods in detecting surface defects such as glass fibre imprints, resin build-up and wrinkles. Therefore, in this paper, a machine vision-based method is proposed to detect surface defects of glass fibre composites. The method designs an automatic inspection platform using two high-resolution line scan cameras for image acquisition. The eight directional templates of the kirsch operator are used to convolve the derivatives of the image pixel points respectively, and the largest template is selected to determine its edge direction, and the detection of surface defects is achieved by combining with the canny operator. The experimental results show that the proposed algorithm can well suppress noise interference, improve the accuracy of edge localization and detection, and well retain edge information while avoiding pseudo-edges.
    Keywords: surface defect detection; computer vision; glass fibre composites; Canny edge detection; Kirsch operator.

  • Analysis and control for ultralow frequency oscillation damping caused by asynchronous networking mode   Order a copy of this article
    by Renqiu Wang, Shangyu Tian, Hongjian Shi, Feiao Li, Yuanyi Kang 
    Abstract: The ultralow frequency oscillation damping problem caused by asynchronous networking mode is investigated for Chongqing-Hubei asynchronous grid. The negative damping problems offered by governors are investigated. The electromechanical transient model of the voltage source converter (VSC)-high voltage direct current (HVDC) for the Chongqing-Hubei asynchronous grid is constructed. Fault modes that cause ultralow frequency oscillation after VSC-HVDC are analysed by using the Power System Analysis Software Package (PSASP), because faults in asynchronous grid often result in the ultra-low frequency oscillation damping. An additional damping controller of the VSC-HVDC and its small signal model are proposed, and the mechanism of the additional controller which increases the system damping is also analysed. The simulation results show that low frequency oscillation can be effectively suppressed by using the provided controller in this paper.
    Keywords: ultralow frequency oscillation; asynchronous grid; additional damping controller; VSC-HVDC electromechanical model.

  • Identification of residual disease followed by trade-off analysis between drug optimisation, MRD and sustenance of normal haematopoiesis under maintenance chemotherapy in childhood acute lymphoblastic leukaemia   Order a copy of this article
    by Durjoy Majumder 
    Abstract: Acute Lymphoblastic Leukaemia (ALL) is a commonly occurring cancer in children, and relapses in many cases. Hence to remove (minimal) residual leukaemia or disease (MRD), a maintenance chemotherapy schedule is conducted for two years after intensive chemotherapy. MRD detection occasionally fails owing to the mutability behaviour of leukemic cells or their aberrant marker expression, and the presence of MRD in very minor amount enhances the chances of relapse in the long term. Application of higher drug dose during the maintenance phase may remove MRD, but produces drug-related toxicity. Bone marrow biopsy is required for MRD detection. Here, a peripheral blood based control theoretical model is proposed to detect the presence of MRD. Moreover, the model-based eigen and trade-off analysis could provide a guidance in clinical decision making to optimise the maintenance chemotherapeutic regime (both dose and duration) for individual ALL patients.
    Keywords: delay ordinary difference equation; drug application control; drug optimisation; chemotherapy in leukaemia; clinical decision support system.

  • Adaptive modified super-twisting sliding mode control based on PSO with neural network for lateral dynamics of autonomous vehicle   Order a copy of this article
    by Rachid Alika, El Mehdi Mellouli, El Houssaine TISSIR 
    Abstract: In this article, we have developed a strategy for controlling the lateral dynamics of an autonomous vehicle. The bicycle model of the autonomous vehicle is used. In order to improve the systems performance, we take a new dynamic surface of the sliding mode and a novel expression of the super twisting part of the controller. The parameters of the controller are determined using the particle swarm optimisation (PSO). The objective of this strategy is to follow the reference trajectory of the autonomous vehicle while reducing the lateral displacement error. The steering angle is the control input, the output of this system are the lateral displacement and the yaw angle. The radial basic function neural network (RBFNN) is used to approximate the unknown nonlinear dynamic. Simulation results show some improvements over the literature.
    Keywords: autonomous vehicles; STSMC; PSO; RBFNN; nonlinear dynamic; path planning; Lyapunov’s stability theory.

  • A fuzzy enhanced adaptive PID control algorithm for quadrotor aircraft   Order a copy of this article
    by Wei Li, Kai Zhang, Chunpeng Zhang, Qiang Wang, Yi Zhang 
    Abstract: A fuzzy enhanced adaptive PID control algorithm is designed for quadrotor Unmanned Aerial Vehicles (UAVs). An ideal quadrotor dynamic model is established through the dynamics analysis of a quadrotor first. To verify the effectiveness of the proposed control strategy, both the hovering and trajectory tracking simulations are carried out with this method. Experiments and simulations show that the designed controller can perform well in various conditions, and the tracking error can be limited to 0.41 meters under a disturbance condition. The comparison results with the traditional PID control algorithm also prove the overall dominance of the proposed controller.
    Keywords: fuzzy enhanced adaptive; quadrotor aircraft; under actuated; double closed-loop PID.

  • Chaotic Harris Hawks optimisation based fuzzy lead lag TCSC and PSS with coordinated control design for enhancement of power system transient stability   Order a copy of this article
    by Asit Kumar Patra, Sangram Mohapatra 
    Abstract: This paper investigates the application of the chaotic Harris Hawks optimisation (CHHO) technique for the tuning of a coordinated control of fuzzy lead lag based TCSC controller with fuzzy PSS power system. The eigenvalue and simulation results of the proposed CHHO based optimised TCSC controller are presented and compared with a coordinated control of lead lag TCSC controller with PSO, DE and GSA optimised lead lag controller under various cases of operating conditions and disturbances in SMIB power system. The proposed CHHO-based fuzzy coordinated controller is compared with CHHO-based lead lag TCSC coordinated control of same power system to check the effectiveness and robustness analysis. Finally, the proposed design approach is extended to a multi-machine test model system to demonstrate how the coordinated control of fuzzy lead lag TCSC damping controller with fuzzy power system stabilises and damps out oscillations in power system to improve transient stability performances.
    Keywords: TCSC; power system stability; fuzzy lead lag damping controller; multi-machine power system. chaotic Harris Hawks optimisation.

  • Controlling and stabilization of remotely operated underwater vehicle   Order a copy of this article
    by Fahad Farooq, Noman Ahmed Siddiqui, Amber Israr, Zain Anwar Ali 
    Abstract: Remotely operated underwater vehicles (ROVs) play a significant role in deep and shallow water missions for exploration, inspection, and extraction. The motions of ROV are guided and controlled by a human pilot present on a surface through a single cord providing power. This study presents the mathematical modelling, kinematic model, and hydrodynamic model of the designed underwater vehicle. It also designs proportional, integral, and derivative (PID) with the nonlinear observer model for ROV which helps in controlling and stabilising its position. The PID controller helps in controlling the altitude of the vehicle while a nonlinear observer model with PID controls and stabilises the attitude. The simulation results show that the designed control scheme is highly accurate and effective. It also shows higher stability and better transient response.
    Keywords: ROV controlling; underwater vehicle; PID.

  • Mittag-Leffler stability analysis for time-fractional hyperbolic systems with space-dependent reactivity using backstepping-based boundary control   Order a copy of this article
    by Yanjiu Zhou, Baotong Cui, Bo Zhuang, Juan Chen 
    Abstract: This paper presents the Mittag-Leffler stability analysis for a controlled time-fractional hyperbolic system with space-dependent reactivity via the backstepping method. The main work of this paper is divided into two parts: 1) the backstepping-based boundary controller design to deal with unstable source terms; 2) the Mittag-Leffler stability analysis by the time-fractional Lyapunov method. For the numerical solution, the implicit Euler finite difference method is applied, together with the family of characteristic curves to solve the kernel partial differential equation and the method of discretizing the Caputo time-fractional derivative. Finally, two examples are given to illustrate the accuracy of the algorithm for calculating the kernel function by contrast with corresponding analytic solutions. A numerical example is shown to validate the effectiveness of the proposed controller.
    Keywords: Mittag-Leffler stability; time-fractional hyperbolic system; backstepping; boundary control.

  • Structural strength evaluation of injection production string in underground gas storage   Order a copy of this article
    by Peng Sun, Zhaomin Li, Zhikai Su, Xiaoxuan Zhang 
    Abstract: Underground gas storage is the most economical and effective means to ensure seasonal peak shaving and stable gas supply. In order to solve the problem that the pipe string is easy to cause fatigue failure due to various loads in the underground, and ensure the safety and normal operation of the gas storage. In this paper, the multi period alternating load of injection production string is analysed. The theoretical analysis is carried out from two aspects: the analysis of string pressure field and the analysis of string temperature field during injection production. The validity of the theory is verified by an example.
    Keywords: injection production string; strength evaluation; pressure analysis; temperature analysis.

  • Hydrogen for railways: design and simulation of an industrial benchmark study   Order a copy of this article
    by Luca Pugi, Lorenzo Berzi, Michael Spedicato, Francesco Cirillo 
    Abstract: Electrified railway systems are probably the most sustainable way to move people and goods, especially for ground connections over short and mid distances. Hydrogen and battery-operated trains represent a feasible solution to increase the sustainability of railway lines that are currently not electrified and consequently operated with fossil-powered units. This work investigates, on a benchmark test case, the advantages and critical aspects of the proposed technology within realistic design constraints. The proposed train layout is innovative with respect to current literature because the composition is longer and storage is arranged to make faster and easier system refuelling. The paper focuses on three aspects that have proven critical for the design: encumbrances of hydrogen storage, additional consumptions introduced by auxiliaries during train stops and other preparation phases, and the real orography of Italian lines, which deeply affects the autonomy of the train.
    Keywords: hybrid railway train; fuel cell train; hydrogen for railways; mechatronics.

  • Time series modelling of a radial-axial ring rolling system.   Order a copy of this article
    by Oscar Bautista Gonzalez, Daniel Rönnow 
    Abstract: In the present work, a digital twin of a radial-axial ring rolling machine was built by modelling the time series of the positions of the tools and control signals rather than the metrics of the produced rings, as performed in previous studies. Real data from the industry was used for modelling. The used model selection methodology is shown in detail to replicate such work for similar systems in the steel industry. The modelling results of ARX, ARMAX and orthonormal basis model structures are shown; additionally, they were validated considering SISO and MIMO systems. The modelling results were better when the subsystems considered were ARMAX and MISO than when ARX and SISO were taken into consideration. The best modelling results were obtained when physical knowledge was included in the model structure. Lastly, it was found that the model error of the horizontal subsystem could be used for predictive maintenance.
    Keywords: radial-axial ring rolling; steel industry; grey box modelling; system identification; MIMO systems; time series.

  • Synchrophasor assisted load frequency control of an interconnected system with multiple fuel inputs using honey badger algorithm   Order a copy of this article
    by Alok Priyadarshi, K.B. Yadav, Vishal Rathore 
    Abstract: Appropriate design of controllers is primarily required for load frequency control (LFC). To achieve better LFC, controller parameters need to be tuned properly. Consequently, a honey badger algorithm (HBA) based controller is designed for LFC of interconnected system with multiple sources in this paper. The frequency deviations (FDs) and tie-line power deviation are considered as input signals to controllers. These deviation signals measured by synchrophasor technology are transferred via communication channel. The time-delay occurred during signal transfer is compensated by Pad'e approximation in this work. The minimization of sum of integral-time-absolute-error (ITAE) of deviations is considered as objective function. The performance of proposed HBA based controller is validated under different test case scenarios of varying step load perturbations. The obtained results are compared with the results reported in literature. Time-domain simulations are presented for each considered cases. Additionally, the performance of proposed controller is tested for random step load variations.
    Keywords: synchrophasor; load frequency control; honey badger algorithm; interconnected system; communication time-delay.

  • Recursive algorithm for interaction prediction in Hammerstein system identification with experimental studies   Order a copy of this article
    by Pawel Mielcarek, Grzegorz Mzyk 
    Abstract: The paper presents a fully recursive algorithm for building a nonlinear block-oriented model of a dynamic system on the basis of noise-corrupted data. Hidden internal signal in the Hammerstein structure is firstly predicted to compute the best possible model of the second (linear dynamic) block of the system. Asymptotically, the algorithm reaches an equilibrium point when the predictor becomes equivalent to the characteristic of the nonlinear block. Nonlinear static element is treated as a black box, and the predictor is based on nonparametric kernel regression or orthogonal expansion estimation method. The crucial contribution lies in the fact that the algorithm computes the offset (bias) between the input-output regression function and the nonlinear characteristic, which allows to get optimal model of the whole system. Experimental studies include both iterative convex optimization procedure and its recursive version, wherein measurement data need not to be stored in memory. As a real data example - thermal analysis of chalcogenide glasses was modelled with an algorithm updated to the Hammerstein system with ARMAX block.
    Keywords: interaction prediction method; Hammerstein system; system identification.

  • System enhancement on perturbations and wind gusts for a twin-rotor helicopter using intelligent active force control   Order a copy of this article
    by Sherif I. Abdelmaksoud, Musa Mailah, Tang H. Hing 
    Abstract: Models of rotorcraft are classified into different categories, and today, the twin-rotor helicopter is considered one of the most versatile flying machines and has attracted many researchers from different disciplines. However, it is a multivariate, highly nonlinear, and strongly coupled model. Also, its performance could be further compromised when it is operated under disturbances or uncertainties. This study presents intelligent control schemes based on a technique called active force control employing the iterative learning algorithm and fuzzy logic. Various types of disturbance, including the sinusoidal wave, pulsating, and Dryden wind gust model disturbances, have been introduced to test the feasibility of the suggested control schemes. Simulated findings show that the proposed AFC-based schemes are effective against disturbances while maintaining system stability. Results indicate that the PID-ILAFC scheme enhances the performance of the twin-rotor helicopter by approximately 70% for pitching motion and almost 30% for yawing motion, under different disturbances.
    Keywords: twin-rotor helicopter; TRMS; UAV; Euler-Lagrange method; active force control; PID controller; iterative learning control; fuzzy logic; Dryden wind gust; disturbance rejection.

  • Vector control strategies of synchronous reluctance motor: constant current control, MTPA, MTPW, and MPFC   Order a copy of this article
    by Yassine Zahraoui, Mohamed Moutchou, Souad Tayane 
    Abstract: This paper presents different vector control strategies in order to improve the performance of a synchronous reluctance motor. As the torque control is directly related to the current control, many strategies can be implemented. Depending on the criterion to be optimised, there are therefore many strategies. The suitable control strategy choice is mainly determined by the way the current reference values will be defined. For that purpose, four techniques are detailed: constant current control, maximum torque per ampere; maximum torque per Weber, and maximum power factor control. All these techniques have been simulated in MATLAB/Simulink, and precise comparison of their characteristics is brought out. The obtained results are satisfactory and good performance is achieved, such as response time, torque ripples reduction, and current improvement. These results will help in deciding which of the four-vector control strategies can be employed in high-performance drive applications, and when and under what conditions.
    Keywords: synchronous reluctance motor; vector control strategies; constant direct current control; constant current angle control; maximum torque per ampere; maximum torque per weber; maximum power factor control; ripple reduction.

    by Michael Todinov 
    Abstract: New results related to the reliability of common systems with interchangeable redundancies at a component level have been obtained by deriving and interpreting a new algebraic inequality. It is shown that for systems with interchangeable redundant components, the system reliability can be increased by asymmetrical arrangement of the redundant components. The system reliability corresponding to asymmetrical arrangement of the redundant components is always superior to the system reliability corresponding to a symmetrical arrangement. For the inequality of the additive ratios, a novel probabilistic interpretation is provided which resulted in a powerful decision strategy for improving the probability of an event occurring with mutually exclusive events. Using this result, a counter-intuitive strategy has been developed for improving the probability of purchasing a reliable product from a set of suppliers delivering the same numbers of reliable products together with unknown numbers of unreliable products. Finally, through geometrical interpretation, new algebraic inequalities have been derived which provide a tight lower bound for the classical root-mean square inequality and a tight upper bound for the classical harmonic mean inequality.
    Keywords: dual active redundancy; inequality of the additive ratios; interpretation; additive quantities; system reliability; mutually exclusive events.

  • A computer vision monitoring for human fall using visible light camera and thermal imager   Order a copy of this article
    by Baolong Yuan, Yanhui Wang, Xin Wang 
    Abstract: In order to solve the problems of image blur, uneven illumination and object occlusion in visual monitoring, a human fall detection algorithm based on visible light camera and thermal imager is proposed in this paper. Firstly, the visible light and thermal images are denoised to reduce the interference of noise. Secondly, the skeleton and joint coordinates of the human body are extracted through the lightweight human posture recognition model. Finally, three human posture parameters are designed as recognition features to achieve accurate fall recognition. The method is verified on self built data sets and public data sets. The experimental results show that the accuracy of the method is 0.93 and 0.94, respectively. Compared with the most advanced algorithms, the proposed method has higher accuracy and better real-time performance.
    Keywords: fall detection; deep neural network; multi-source image fusion; computer vision.

  • Mathematical modelling, bifurcation analysis, circuit design and FPGA implementation of a 5-D hyperchaotic weather fluctuation model with a line of equilibrium points
    by Sundarapandian Vaidyanathan, Irene Moroz, Esteban Tlelo-Cuautle, Aceng Sambas, Ciro Fabian Bermudez-Marquez, Samy Abdelwahab Safaan 
    Abstract: High-dimensional hyperchaotic systems are known to have several applications in engineering owing to their high complexity. This work reports the finding of a new 5-D hyperchaotic weather fluctuation model, which is constructed by means of introducing two state feedback controllers in the 3-D Vallis weather fluctuation model (1986). The new hyperchaotic system has a line of equilibrium points. Hence, it has hidden attractors. We carry out a detailed bifurcation analysis with standard tools such as bifurcation diagrams and Lyapunov exponents to study the intrinsic properties of the 5-D weather fluctuation model with respect to changes in the system constants. Next, we design an electronic circuit of the 5-D weather fluctuation model using MultiSim. The new 5-D hyperchaotic weather fluctuation model is implemented herein by applying two one-step numerical methods, viz. Forward Euler and Trapezoidal rule. Experimental attractors for the 5-D hyperchaotic model are shown from an oscilloscope.
    Keywords: Modelling; bifurcation; chaos; hyperchaos; hyperchaotic systems; equilibrium points; linernequilibrium; stability; circuit design; FPGA design.

  • Unmanned Aerial Vehicles for Touristry Purpose- A Comprehensive Survey on Its Security and Safety Aspects
    by Xiufang Zhang, Yujun Zhu, Shuai Wang 
    Abstract: Numerous tourist destinations and attractions, including national parks, canyons, seaside locations, etc., have experienced an increase in theft, kidnapping, and property loss instances. Due to the limitation, there are not enough security personnel to cover the vast coastline region. Unmanned aerial vehicles are one method that may be used to patrol such areas. This type of use will not only protect the tourist destination but also advertise it globally. This research proposed an effective optimization technique to determine the precise number of UAVs needed to carry out security and safety of tourists. In simplified terms, the reader will be able to obtain an optimum approach to deal with the constraints of UAVs, such as long-duration missions with improved economic system design and operational scheduling concerns concurrently. The economic system design and operational plan are also presented, along with a clever hypothesis based on information.
    Keywords: Tourism; unmanned aerial vehicle UAV; safety; security; economic investment; operational schedule; and optimization model.

  • Design of Decentralized PI/PID Control Algorithm for a Benchmark Continuously Stirred Tank Reactor System using Frequency Domain Specifications
    by Achu Govind K R, Subhasish Mahapatra 
    Abstract: This paper uses frequency domain specifications to design a decentralized PI/PID controller for a benchmark continuously stirred tank reactor (CSTR) industrial system. The primary objective of the work is to control the parameters of CSTR within the operating regions by regulating the temperature and reactor concentration. The decentralized control is designed by considering a decoupled CSTR system in which the diagonal elements are the FOPDT systems. Besides, decouplers are designed to reduce the loop interactions. The controllers are designed based on the frequency domain specifications such as gain margin and phase margin. The robust stability is analyzed by considering multiplicative input and output uncertainties. A concise comparison is made between the proposed technique with existing methods to show the efficacious behaviour of the developed control algorithm. It is envisaged that the proposed control algorithm exhibits better servo and regulatory response compared to the existing techniques.
    Keywords: Decentralized control; Process Control; FOPDT model; Uncertainty; Robustness;

  • Data-Driven Identification for Nonlinear Dynamic Systems
    by Sergey Lyshevski 
    Abstract: For nonlinear dynamic systems, this paper investigates problems of identification and parameter estimation. These problems are critical in aerial, electromechanical, robotic and other systems. Analysis and control of physical systems imply the use of adequate mathematical descriptions, ensuring sufficient fidelity. Particular challenges occur if systems exhibit oscillations, limit cycles and instabilities. We apply multivariate polynomials and model-to-system mismatche measures to solve identification problems during dynamic governance. Physics-consistent nonlinear models are parameterized, truncated and validated using matrix factorization schemes and algorithms. Heterogeneous measurements adverse the information content and obscure observed data. Singular value decomposition ensures algorithmic convergence and validity. Using simulations and experimental studies, a data-driven identification concept is demonstrated and validated.
    Keywords: Dynamic systems, estimation, identification, nonlinear systems

  • A data transmission protocol for WSN based on multi-strategy improved whale optimisation algorithm
    by Xi Chen, Tao Qin, Wei Wei, Yuancheng Fan, Xuemei Luo, Jing Yang 
    Abstract: This paper is a study of routing protocols for wireless sensor network (WSN) based on the whale optimisation algorithm (WOA), which has problems such as slow convergence, low convergence accuracy and the tendency to fall into local optimality. Firstly, a multi-strategy WOA named CNGS-WOA is proposed, which includes chaotic mapping, non-linear processing of convergence factor and golden sine partition. The simulation results show that the CNGS-WOA has obvious advantages in terms of search accuracy and stability. Secondly, a data transmission protocol named CNGS-WOA-RP is proposed based on the improved WOA. By comparing four aspects of network clustering effect, network life cycle, network residual energy and network energy consumption balance, it's shown that the data transmission protocol CNGS-WOA-RP can effectively reduce and balance network energy consumption, and has greater advantages in extending network It has greater advantages in extending the network lifetime.
    Keywords: Data transmission; Whale optimisation algorithm; Minimum energy consumption; Optimal clustering; Energy balance.

  • Real-Time Data Acquisition for Anti-Lock Brake System Test-Rig with Intelligent Controller
    by Mohammed H. Al-Mola, Musa Mailah, Mohd Azli Salim 
    Abstract: Data acquisition (DAQ) is the link between the physical phenomena of any dynamic system and the computer. This device supplies the associated research applications with high demonstration I/O, industry primary innovations, and lower performance gains in software. This paper presented the design of an anti-lock braking device for ground vehicles within the laboratory and low-cost assembly compared to other designs and the superior control performance of the proposed technique. It uses DAQ for calculation and LabVIEW simulation software to analyze, display, and store data in real-time. The experimental set-up with AC motor assembled with the lower cast iron wheel, rubber vehicle wheel, brake pedal, and attached with the hydraulic actuator. The DAQ operated as a link between the computer and the apparatus to demonstrate the performance of the suggested dynamic system. The intelligent active force control technique was merged into the control system and the physical performance of the test rig was presented digitally in LabVIEW software. The results demonstrate the efficiency and favorable reaction of the proposed control approach with the test rig offering superior tracking of 0.21 slip ratio and steady braking on dry roads with a 12.49% reduction in braking distance when compared to other approaches.
    Keywords: ABS system, Data Acquisition (DAQ), Active Force Control (AFC), wheel slip, stopping distance.

  • Quantized Global Prescribed Performance Control of Unknown Strict-Feedback Systems
    by Wei Ding, Jin-Xi Zhang 
    Abstract: This paper is concerned with the reference tracking problem for the unknown strict-feedback systems subject to unmatched disturbances under quantized control. The quantization error and the model uncertainty yield challenges in fast and accurate tracking control. A quantized robust global prescribed performance control approach is given to address the problem. It achieves output tracking with arbitrarily predefined settling time and accuracy and ensures boundedness of all the signals involved in the control system for any initial condition. Furthermore, the proposed control exhibits signifificant simplicity. It does not invoke the techniques of approximation, identifification, estimation, etc, to deal with model uncertainties. On the other hand, there is no need to calculate the intermediate control signal derivatives in the recursive design. The simulation study on a jet engine compressor illustrate the above theoretical findings.
    Keywords: Control Simplicity; Global Stability; Nonlinear Systems; Prescribed Performance; Quantized Control.

Special Issue on: Soft Computing for Data Analytics, Image Classification and Control

  • Software Reliability Testing Coverage Model using Feed-Forward Back Propagation Neural Network
    by RITU BIBYAN, Sameer Anand, Ajay Jaiswal, Anu Gupta Aggarwal 
    Abstract: The paper presents Software Reliability Growth model (SRGM) with testing coverage which covers both detection as well as correction process under imperfect debugging. The estimation is done using feed forward back propagation artificial neural network. Many researchers have studied the importance of modeling fault detection instead of modeling fault correction. We have proposed generalized testing coverage model by adopting different testing coverage for both the processes. We have also compared proposed with existing traditional models based on three failure data sets. Different performance criteria like goodness of fit, accuracy of the model, mean square error (MSE), and Coefficient of determination (R2) are evaluated for the datasets. The comparison results shows that the model proposed in this paper provides efficient accuracy than the existing traditional models.
    Keywords: Software Reliability; Testing Coverage; Machine Learning; Feed-forward; Back-propagation; Neural Network.

    by Kriti Vashistha, Anuja Bokhare 
    Abstract: One of the most difficult tasks in medicine is predicting heart disease. Every minute, roughly one person dies from heart disease in the modern era. The heart is the second most important organ in the human body after the brain. Predicting the occurrence of heart diseases is the most important work in the medical industry. This is where machine learning and data analytics comes into play. Moreover, the medical industry is able to collect huge amount of data on a monthly basis. This information can be used to forecast the occurrence of future diseases. According to the previous work for this research authors have mostly worked on algorithms like KNN, SVM and Nave Bayes. In this study, the proposed technique analyses three different algorithms: decision trees, random forests, and logistic regression. After correctly training and evaluating the models, we noticed that random forest had the highest accuracy of 83 percent, followed by logistic regression with 81 percent, and decision tree with 77 percent. The most important factors in prediction were found to be age, Trestbps, cholesterol, and Oldpeak. For future work we would enhance the accuracy of our model which will hopefully one day be able to help battle the ever-growing problem of coronary artery disease.
    Keywords: medical industry; heart disease; random forest; decision tree; logistic regression; machine learning.

  • Optimisation of target coverage in wireless sensor networks using a learning automata approach   Order a copy of this article
    by Haribansh Mishra, Anil Kumar Pandey, Bankteshwar Tiwari 
    Abstract: Wireless Sensor Networks (WSNs) technology is employed in multiple areas, such as battleground surveillance and home security. In WSN, most algorithms are based on the Maximum Cover Set (MCS) for energy-efficient target coverage (TC). But it generates the NP-complete problem of constructing maximal CS. These cover formations consume more energy because each node participates in the building of sets. To reduce the average energy consumption of networks, we propose a learning automata based on a scheduling algorithm called Self-Adaptive Minimum Energy Consumption algorithm (SAMECA). The SAMECA assists each sensor to choose the proper state (active or sleep) at any given time. The purpose of SAMECA is to increase the network lifetime by maximising the sleep state presence of nodes. Besides, it ensures that fewer sensors are required to cover all the targets. The results indicate that the SAMECA is a decent option to analyse all the targets by consuming less energy power.
    Keywords: learning automata; network lifetime; sensor; wireless sensor network.

  • An efficient data retrieval method for grid blockchain   Order a copy of this article
    by Caijun Zhang, Qianjun Wu, Jiayi Lang, Huafei Yang, Xiaolong Wang, Kaiqiang Xian, Jingqiu Zhang 
    Abstract: The blockchain-based power grid integration business systems (PG-IBS) are increasing rapidly. However, owing to the limitation of blockchain, these systems have the problem of low data retrieval efficiency. To solve this problem, through careful investigation and analysis, an efficient data retrieval method for power grid blockchain (EDRM-PGB) is proposed in this paper. EDRMPGB rebuilds an efficient retrieval index structure TIS (Transaction Index Structure) for a PG-IBS, while maintaining compatibility with the original system. TIS index structure is built on two data structures BABF (Blockchain Account Bloom Filter) and BTTI (Binary Tree with Transaction Information). Based on the structure, EDRM-PGB efficient retrieval algorithm is designed. EDRMPGB's feasibility is verified by the prototype system implementation and performance simulation. Simulation results show that, compared with the traditional retrieval method, EDRM-PGB can greatly improve the data retrieval performance of PG-IBS. Meanwhile, it also has advantage of sharing of index files easily.
    Keywords: data retrieval; blockchain; power grid; retrieval algorithm.

  • Classification of imbalanced hyperspectral images using ensembled kernel rotational forest   Order a copy of this article
    by Debaleena Datta, Pradeep Kumar Mallick, Mihir Narayan Mohanty 
    Abstract: Hyperspectral image classification suffers from an imbalance in the samples belonging to its different classes. In this paper, we propose a two-fold novel approach named Oversampler+Kernel Rotation Forest (O+KRoF). First, synthetic minority oversampling (SMOTE) and adaptive synthetic oversampling (ADASYN) techniques are employed on original data to balance it owing to their adaptive nature in the majority and minority samples. Finally, the ensembled KRoF classifier is applied, a combination of unpruned Classification and Regression Trees (CART) as its base algorithm and kernel PCA for feature reduction and most significant nonlinear spatial-spectral feature selection. Furthermore, we designed a comparison study with frequently used oversamplers and related state-of-art tree-based classifiers. It was found that our ensemble model is suitable and performs better than earlier works as it attains 90.92%, 97.1%, and 93.39% overall accuracies when experimented on the benchmark datasets Indian Pines, Salinas Valley, and Pavia University, respectively.
    Keywords: hyperspectral images; resampling; synthetic oversampling; tree-based classifiers; modified rotation forest.

Special Issue on: Recent Advances on Learning-Based Control Theory and Application

  • A survey on modern trends of low power long range network applied to IoT applications   Order a copy of this article
    by Muhammad Aamir Khan, Zain Anwar Ali, Muhammad Shafiq 
    Abstract: In recent years, Long Range (LoRa) networks are gaining popularity in all areas of engineering and also demands to minimise the structure of the network to cover a wide geographical area with extremely low power consumption. LoRa network is designed for the broad range communications capacity especially suitable for Internet of Things (IoT) applications. In the wide context of communication channels, LoRa has the significant support applications for long distance multi-hop network with the minimise packet size and low latency. This paper presents the recent advancements and technical analysis of LoRa network in different IoT applications. The paper also reviews performance and challenges faced by LoRa networks under different scenarios. The paper also involves the findings and restrictions of the proposed work to help research scholars for the network optimisation in order to improve the performance parameters for any environment.
    Keywords: long range network; low power consumption; internet of things; communication channels.

  • Experimental validation of an output feedback controller based on an integral and adaptive backstepping technique for a fuel-cell power system.   Order a copy of this article
    by Soukaina Nady, Hassan EL Fadil, Fatima Zahra Belhaj, Abdessamad Intidam, Mohamed Koundi, Zakariae El Idrissi 
    Abstract: The present work establishes a comparison between two controllers based on a backstepping approach for a fuel-cell power system. The load resistance representing the impedance of the DC bus is assumed to be unknown and can change. Besides, the internal fuel-cell voltage is not accessible for measurement. Therefore, to cope with these two issues, two output feedback controllers are designed using a backstepping technique. The first controller uses an integral action while the second one is an adaptive version of the former. It is formally shown using theoretical analysis and simulation that the obtained controllers achieve all control objectives. A comparison between the two controllers shows that, when they are correctly tuned, both behave almost similarly. Nevertheless, we noted the weak supremacy of the adaptive version over the integral version in terms of rapidity. A laboratory prototype is built to show the effectiveness of the proposed control approaches.
    Keywords: fuel cell; dc-dc buck power converters; nonlinear control; adaptive control; Lyapunov stability; output feedback; backstepping technique.

  • PI-based hybrid control for load-stress management of a fuel cell-based hybrid power system   Order a copy of this article
    by Kumaril Buts, Lillie Dewan, M.P.R. Prasad 
    Abstract: The proton exchange membrane-based hydrogen fuel cell (PEMHFC) provides electrical power with zero carbon emission. It is an electrochemical device (viz batteries) that delivers a DC power supply. The life-cycle of the PEMHFC is significantly affected by the stack current stress, in particular, during high load demand when the current stepping up. This results in fuel/oxygen starvation and is liable to slow electrochemical reaction dynamics. Therefore, PEMHFC stack current regulation is crucially important along with fulfilling the power need. In this paper, a Proportional and Integral (PI)-based hybrid control system is proposed to achieve the current limiting and maintain the voltage level simultaneously for PEMHFC and battery-supported hybrid systems during the demand of the variable loads. The proposed control approach is first verified in MATLAB simulation with variable loads and then implemented at the hardware level in the LabVIEW environment.
    Keywords: coordinated control; cascaded control; hybrid control; average-value converter model; power management; proton exchange membrane hydrogen fuel cell.

  • Establishing a calculus learning application   Order a copy of this article
    by Ting-sheng Weng 
    Abstract: Mobile learning enables students to use handheld devices to learn everywhere. Mathematics is an important basic tool discipline and a vital indicator of national quality. This study used the Android Studio programme to develop a calculus learning application. Adopted animation software combined with calculus content is used to build a learning channel and platform readily available to learners through hand-held mobile devices. With this, learners can learn calculus dynamically on smartphones. During the COVID-19 pandemic, students were unable to attend classes. As a result, many countries had to implement distance education or mobile learning. Through the 0ground system in the application, teachers can query students' learning records at any time. This fosters an understanding of the learning situation. Counselling can be provided for students who are not on the teaching site. Students can move at any time to improve learning efficiency by using the smartphone teaching and learning system.
    Keywords: App; calculus; learning system; mobile learning; animated teaching material; COVID-19 pandemic; distance education; game-based learning; learning achievement; software engineering.

  • Research on exchange rate forecast based on MLR-ELM model   Order a copy of this article
    by Yi Peng, Kang He, Qing Yu, Yanan Chen 
    Abstract: This paper introduces a new model to predict the exchange rate. The model is a combination model of the multiple linear regression model (MLR) and the extreme learning machine model (ELM). The RMB-USD exchange rate is the object of prediction. Firstly, the sample data are pre-processed and divided into a training set and a test set; then a linear regression equation is created for the training set. The predicted value of the MLR model and other selected independent variables are the input data of ELM, which is determined by the training set. Secondly, the test set data is tested with parameter set obtained from the training set, and the optimal parameters of MLR-ELM model are determined by the performance of the training set and the test set. Finally, the exchange rate is predicted. The simulation results suggest that MLR-ELM model have a better prediction than the multiple linear regression model.
    Keywords: exchange rate forecast; multiple linear regression model; extreme learning machine model.

  • Impacts of countermeasures on driving performance through drivers' attention in rural curves: a driving simulation study   Order a copy of this article
    by Hongyue Wu, Yunfeng Chen, Weinan Gao, Osahon Iroghama, Junan Shen 
    Abstract: Drivers attention is a critical factor influencing traffic safety. However, limited work explained the relationships between countermeasures, attention, and driving performance in rural curves. This study explores the impacts of countermeasures on driving performance through attention under different weather conditions and traffic flows using an experiment with a driving simulator and an eye tracker. The multivariate regression analysis verified the mediating role of cognitive workload measured by changes in pupil diameter on the relations between countermeasures and driving performance. Then, all the countermeasures were effective in ensuring driving performance. The rank of effectiveness was provided. In addition, the effectiveness of countermeasures varied across weather conditions and traffic flows. The paper contributed new insights to the relationships between countermeasures and driving performance by incorporating drivers attention. In practice, recommendations were provided to improve traffic safety in rural curves under different external environments.
    Keywords: countermeasures; rural curve; drivers' attention; driving performance; traffic safety; driving simulation; eye tracker; eye movement; multivariate regression analysis; mediating effect; weather conditions; traffic flow.

  • Jaya algorithm-based optimal control for inverted pendulum   Order a copy of this article
    by Vinayak Kumar, Ruchi Agarwal 
    Abstract: The paper proposes an optimal controller to regulate highly non-linear inverted pendulum (IP) cart system. It comprises force as a single input and two outputs i.e. cart position and pendulum angle, thereby controlling of IP cart system is a tedious task for the control engineers. The paper proposes an optimal controller that is composed of linear quadratic regulator (LQR) and proportional, integral and derivative (PID) controller and its controllers gains, e.g. LQR and PID are optimised with the Jaya algorithm. The performance of the proposed controller is evaluated and compared with LQR based PID controller without any optimisation algorithm under steady state as well as transient state condition under MATLAB-Simulink environment. The Jaya based optimal controller shows better performance as compared with the LQR-based PID controller in terms of lower value of rise time, settling time, and peak overshoot and undershoot, etc.
    Keywords: Jaya algorithm; LQR; inverted pendulum cart system.

Special Issue on: Modelling, Prediction, and Control of Complex Systems

  • Research on Noise Field of PMSG Demagnetization Fault
    by Hailiang Zhao, Ran An, Xiangfeng Li, Wei Yang, Zhiyan Zhang, Chengwei Jiang 
    Abstract: In this paper, the mathematical models of the radial electromagnetic force and vibration noise of the PMSG is established, and the influence of the demagnetization fault on them is analyzed theoretically. A 1kW, 12-pole prototype is studied, and the two-dimensional electromagnetic field and three-dimensional noise field models of the PMSG are established, the radial electromagnetic force is used as the excitation to couple the electromagnetic vibration and noise. The operation states of the PMSG under normal and different demagnetization fault conditions are simulated, and the simulation results show that the air gap flux density appears large distortion under the demagnetization fault conditions, and the fundamental wave amplitude decreases, the sound pressure level distribution of the noise field presents a chaotic state, and the sound pressure increases significantly.
    Keywords: PMSG; demagnetization fault; noise field; electromagnetic field.

  • Highly efficient on-line stochastic gradient and sliding window stochastic gradient signal modeling methods for multi-frequency signals
    by Guanglei Song, Ling Xu 
    Abstract: This essay designed the signal parameter identification methodology for the signal which is composed of the sine components and cosine components. With the help of the gradient search, a stochastic gradient modeling method is presented to estimate all of the trait parameters of the multiple sine-cosine components. Further, some improvement schemes are designed to be aimed at enhancing the precision and convergence speed. Moreover, a rolling optimization\r\nloss function based on the cumulated dynamic measurements is proposed to present a highly efficient and high precision signal modeling methodology. Finally, the algorithm emulation is introduced to confirm the feature of the proposed signal modeling methodologies in improving the accuracy of parameter estimation.
    Keywords: Signal modeling; Parameter estimation; Multi-frequency signal; Gradient search.

  • Cooperative spectrum sensing based on locally linear embedding and adaboost in dynamic fading channel
    by Yanhui Wang, Dongliang Bian, Jun Pan 
    Abstract: In mountainous areas and dense forests, the performance of spectrum sensing is largely degraded due to factors such as shadow fading and noise uncertainty, which results in serious consequences of wasting spectrum resources. To overcome these problems, a novel cooperative spectrum sensing method based on locally linear embedding (LLE) and adaboost is proposed. This method addresses the characteristics of dynamically fading channels and does not rely on any a priori information. Firstly, cognitive radio (CR) users with excellent performance are selected to participate in spectrum sensing, while later important information components of nonlinear data in the received signal are obtained through LLE, and finally the excellent classification performance of adaboost is used to achieve accurate sensing of the main user signal. Comparative experiments are conducted in a low SNR environment, the proposed algorithm can effectively obtain the received signal feature information and accurately achieve spectrum sensing.
    Keywords: cooperative spectrum sensing; CR user selection; locally linear embedding; adaboost.

  • A series arc fault diagnosis method based on random forest model
    by Qianhong Hou, Yongxin Chou, Jicheng Liu, Haifeng Mao, Mingda Lou 
    Abstract: The current of series arc fault is too weak to be detected by the circuit breaker, which is one of the causes of electrical fire. Therefore, an intelligent diagnosis method of series arc fault based on random forest (RF) is proposed in this study. Firstly, the high-frequency current signals of six kinds of loads are collected as experimental data. Then, thirteen features were extracted from time domain and frequency domain, and the feature was reduced to four dimensions by principal component analysis (PCA). Finally, a classifier for series arc fault diagnosis is designed using RF. The experimental data in this study are collected by the low-voltage AC series arc fault data acquisition device developed by ourselves. The identification accuracy of series arc fault is 99.95%±0.03%. Compared with the existing series arc fault diagnosis methods, it has higher recognition performance.
    Keywords: Arc fault dectection; Intelligent diagnosis; Random forest; Feature extraction; Principal component analysis.

  • EEG based Epileptic Seizure State Detection using Deep Learning
    by Vibha Patel, Dharmendra Bhatti, Amit Ganatra, Jaishree Tailor 
    Abstract: Artificial intelligence-assisted diagnostics are booming with advanced computing power and technology. An automated approach to detect the seizure state from EEG recordings is highly desirable as the manual approach is tedious, time-consuming, and prone to errors. Our work proposes a hybrid deep learning architecture for automated seizure state detection from long-term patient-specific EEG. The architecture uses one-dimensional Convolutional Neural Network (1D-CNN) and stacked Long Short-Term Memory networks (LSTM). An open-source epilepsy dataset, CHB-MIT, is used in this work for experiments. The synthetic Minority Oversampling Technique (SMOTE) is used for handling class imbalance issues. Our proposed approach achieves an average of 90% accuracy, sensitivity, and specificity with an AUC value of 0.96 and an FPR of 0.10. This performance is remarkable, considering varying EEG channels, channel montages, and EEG durations. Our work facilitates seizure detection devices for faster and more precise decision-making for epilepsy treatment.
    Keywords: Artificial Intelligence; Machine Learning; Deep Learning; Epileptic seizure Detection; Convolutional Neural Network; Long Short Term Memory Network.

  • Simulation and Parametric Optimal Design of Active Radial magnetic fluid Bearing
    by liwen Chen, Jianhua Zhao, xiaochen Wu, jisheng Zhao, Jia Deng 
    Abstract: This paper designs a magnetic-fluid bearing with electromagnetic-static pressure dual support, and designs the structural parameters of the radial magnetic-hydraulic bearing. Based on the optimal bearing capacity, Matlab is used to optimize the bearing cavity diameter and oil film thickness, and it is concluded that the bearing capacity is better when the diameter of the bearing cavity is 10 mm and the thickness of the oil film is 30 ?m. Then, the fluid-solid-thermal coupling analysis of the magnetic fluid bearing was carried out, using Ansys software analyzed the influence of structural parameters on the bearing temperature rising and thermal deformation, and it was concluded that the thermal deformation of the magnetic fluid bearing was the smallest when the oil film thickness was 30 ?m and the axial length of the stator was 45 mm. These lay a theoretical basis for the structural optimization design of the bearing.
    Keywords: Magnetic fluid bearing; Parametric design; Bearing capacity analysis; Fluid-solid-thermal coupling; Structural parameter optimization

  • Lithium battery model online parameter identification method based on Multi-innovation least square
    by Jie Wu, Huigang xu, Peiyi Zhu 
    Abstract: Accurate lithium-ion battery models are important for the accurate estimation of battery states as well as the simulation, design, and optimization of new energy electric vehicles. However, the traditional recursive least squares method(RLS) exhibits disadvantages such as low accuracy and long convergence time when applied to the identification of battery model parameters. In this paper, the second-order RC equivalent circuit model of lithium-ion battery is studied, and the online identification of model parameters by Multi-innovation least squares method is presented, which use Multi - innovation to correct the difference between the observed value output at the previous time and the estimated value of the model identified at the previous time, which extends the single information of the original least square method to multiple innovations. Data collected through HPPC cycle conditions and NEDC conditions experiments. The accuracy and convergence speed of the conventional recursive least squares estimation algorithm is described, to compare the absolute error between the estimated battery port voltage and the real value of the battery with different new interest lengths of the Multi-innovation least squares algorithm. The experimental results show that the Multi-innovation least squares algorithm with longer new interest length has higher accuracy and convergence speed, which verifies the effectiveness and feasibility of the proposed method.
    Keywords: lithium-ion battery, estimation of battery states, RLS, battery model parameters, Multi-innovation least squares, HPPC cycle conditions, NEDC conditions experiments, absolute error