International Journal of Modelling, Identification and Control (70 papers in press)

Regular Issues

• Outlier detection algorithm based on deviation characteristic  
  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.
  
  
• Design of a PEM fuel cell powered autonomous quadcopter  
  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.
  
  
• Universal activation function for data-driven gait model  
  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.
  
  
• Equal-weight and rank-sum-weight based systematic diminution of higher order continuous systems using grey wolf optimisation  
  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  
  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  
  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  
  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.
  
  
• 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  
  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  
  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  
  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  
  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  
  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  
  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.
  
  
• Hydrogen for railways: design and simulation of an industrial benchmark study  
  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.  
  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  
  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  
  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  
  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  
  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.
  
  
• Improving system reliability and the probability of selecting reliable components by interpreting algebraic inequalities  
  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  
  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 tourism purposes: a comprehensive survey on the security and safety aspects  
  by Xiufang Zhang, Yujun Zhu, Shuai Wang 
  Abstract: Numerous tourist destinations and attractions in China, including national parks, canyons, seaside locations, etc., have experienced an increase in theft, kidnapping, and property loss instances. 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 optimisation 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; safety; security; economic investment; operational schedule; optimisation model.
  
  
• Design of a decentralised 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 decentralised 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 decentralised 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 analysed 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 with the existing techniques.
  Keywords: decentralised control; process control; FOPDT model; uncertainty; robustness.
  DOI: 10.1504/IJMIC.2023.10054671
   
  
• 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 mismatched measures to solve identification problems during dynamic governance. Physics-consistent nonlinear models are parameterised, 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 analyse, 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 favourable 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; active force control; wheel slip; stopping distance.
  
  
• Quantised 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 significant simplicity. It does not invoke the techniques of approximation, identification, 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; quantised control.
  
  
• Robust stabilisation for a class of uncertain nonlinear systems with output constraint satisfaction via controller switching  
  by Qi Wang, Ma Ruicheng 
  Abstract: In this paper, we study the problem of robust stabilisation for a class of uncertain nonlinear systems with output constraint satisfaction via controller switching. We first consider two controllers: one is the invariance controller designed by backstepping which is responsible for constraint satisfaction but does not necessarily stabilise the system; the other is the controller which is in charge of stabilisation without taking the output constraint into account. We then introduce a switching law which orchestrates switching between the two controllers to achieve robust stabilisation with output constraint provided the switching signal satisfies certain conditions. The gains of the invariance controller depend on where the invariance controller is switched on and how to determine the gains is also obtained. Finally, an example of an active magnetic bearing system is given to illustrate the effectiveness of the proposed method.
  Keywords: uncertain nonlinear systems; switching; robust stabilisation; output constraint; backstepping.
  
  
• A novel hierarchical-based simulation method for refined calculation of Litz wire structure  
  by Wen Jiang, Yuchuang Sun, Wangzhe Li 
  Abstract: In order to avoid skin effect, Litz wire is a common structure in the field of high-frequency power transmission. The refined Litz wire structure simulation is more accurate for the calculation of current density and electromagnetic force of the wire, which is more conducive to accurately evaluate the stability and safety of the wire. However, the refined simulation often leads to the rise of computer memory. In order to solve the problem of memory rise caused by the Litz wire, a novel low memory calculation strategy of Litz wire refined simulation based on the finite element method is proposed in this paper. Based on proving the feasibility of the calculation strategy in theory, the effectiveness and feasibility of the calculation strategy are verified by simulation and practical tests.
  Keywords: electromagnetic simulation; Litz line; refined simulation of Litz line structure.
  
  
• Proportional integral observer using disturbance attenuation strategy for discrete-time linear singularly perturbed system  
  by Marwa Ltifi, Nesrine Bahri, Majda Ltaief 
  Abstract: This paper deals with the observability bound problem of a discrete-time linear singularly perturbed system (DTLSPS) subject to L2 disturbance and L2 noise. A proper PI observer, known by its robustness, is devised for state estimation, ensuring that the observation error is asymptotically stable and satisfies the Hinfini performance constraint for a proper bound of the singular perturbation parameter based on a quadratic Lyapunov function and the Hinfini norm. In order to design this observer, sufficient conditions expressed in terms of linear matrix inequalities (LMIs) are developed to ensure the robust stability bound of the considered system. This task is also achieved using a quadratic Lyapunov function and the Hinfini norm. Then, using the outcomes of these two tasks, the observability bound of the system is determined. Two simulation examples are then given to validate the proposed strategy.
  Keywords: discrete-time linear singularly perturbed system; noise; disturbance; robust stability bound; observability bound; proportional integral observer.
  
  
• Grid frequency stabilisation under magnitude and generation rate constraints  
  by Hisham Soliman, Abdellah Benzaouia, Farag Ali El-Sheikhi, Kenan Buyukatak 
  Abstract: A new load frequency control (LFC) design in a multi-area power system is introduced in this paper. The proposed design tackles the problem of constraints on both control magnitude and its rate. With this design, the control limits (corresponding to a fully open/closed fuel valve) are not violated. Also, the generation rate constraint (GRC) is kept within the permissible range imposed in practice. Violation of such constraints may lead to instability or damage of mechanical parts. A pole placement method is used to solve this inverse problem. The resulting stabiliser is state feedback plus integral control. The proposed control avoids the complexity in modelling the nonlinear like of the GRC. Unlike other designs, the suggested control represents a link between the pole placement procedure and these constraints. To validate the efficacy of the proposed design, digital simulations for single and two-area power systems are presented in this paper. A comparison is made between the proposed control and the traditional control scheme, which confirms the proposed technique's supremacy.
  Keywords: constrained control; generation rate constraints; load frequency control; positive invariance; pole placement.
  
  
• Advanced control of an autonomous torpedo-type underwater vehicle with integral backstepping techniques in the yaw plane  
  by Hattab Abdellilah, Yahiaoui Kamel 
  Abstract: Underwater robots, especially those that are autonomous, are some of the most difficult systems that require a robust controller to handle well the tasks given to them. The difficulty lies in the variation of the parameters of the autonomous underwater robot (inertia, hydrodynamics), the external disturbances, the nonlinearity of the model to be controlled, and the measurement errors due to the sensors. A robust control law such as the backstepping technique is very demanding for this type of system, thanks to its robustness in the face of disturbances. In this work, we discuss the application of the recoil control theory on the diving autonomous robot system. This article is based on the advanced control of the yaw plane. To improve the performance of our system we make a hybridisation between the integral controller and the backstepping controller. Several simulation tests were performed to test the effectiveness of the proposed commands.
  Keywords: diver robot autonomous; recoil control; integral control; mobile robot.
  
  
• New approach for online parameters identification for non-holonomic mobile robots  
  by Jean Marie Lauhic Ndong Mezui, Dieurdonné Ekang, Donatien Nganga-Kouya, Maarouf Saad, Aime Francis Okou 
  Abstract: The dynamic models that represent robotic systems greatly condition the strategies used for the design of their control systems. The accuracy of the model parameter values can have a significant impact on the closed-loop system performance. This paper proposes an innovative method for the online parameters identification (IOPI) of a non-holonomic mobile robot. The proposed method enables to find the inertia accurately, mass and friction parameters in the robot's model and it does not require the drive wheel input torques to be sufficiently rich signals. The identification algorithm is based on the resolution of a system of linearly independent equations. The number of equations is equal to the number of unknown parameters to be estimated. The simulation results show that with the proposed method, the estimated parameters quickly converge to the real parameters of the non-holonomic mobile robot, contrary to the recursive least squares (RLS) method.
  Keywords: Non-holonomic mobile robot; Parameter estimation; Iterative identification in continuous time of Newton; Recursive least squares method.
  
  
• FEM and Simscape modelling and LQG control of a two-Link rigid-flexible manipulator  
  by Tariq Darabseh 
  Abstract: This study models a two-link rigid-flexible manipulator using two methods: mathematical modelling with Lagrange's equations and the Finite Elements Method (FE model) and constructing the model with MATLAB's Simscape Multibody tool (Simscape Model). The FE model is validated by comparing it to a linearized version of the physical Simscape model, taking into account structural damping, hub inertias, and payload at the flexible link's endpoint. The resonance frequencies of the first three modes are analysed in the frequency domain using both models. The open-loop responses of both models are also compared in the time domain. A linear quadratic Gaussian (LQG) controller with a Kalman filter and integral action is developed and implemented using the Simscape Model. The simulation results using MATLAB show that the proposed method is efficient and practical for joint angle trajectory tracking and flexible link vibration control of the rigid-flexible manipulator. The LQG controller is shown to be more effective in reducing vibrations and enhancing performance of flexible link manipulators when compared to a Proportional-Derivative (PD) controller.
  Keywords: rigid-flexible manipulator; LQG controller; finite element method; Kalman filter; Simscape/MATLAB.
  
  
• A backstepping controller based on RBFNN for mobile manipulator with unknown wheel slippage  
  by Soni Soni, Naveen Kumar 
  Abstract: In this paper, a backstepping-based control scheme for position tracking of the mobile manipulator under the presence of unknown wheel slippage, disturbances, and uncertainties is presented. The proposed control scheme takes the advantages of a backstepping controller because of its ability to handle uncertainties. Due to lack of prior knowledge regarding the dynamic characteristics of the mobile manipulator, smooth nonlinear dynamic functions are unknown, and for estimation of the same radial basis function neural network is used. The adaptive compensator is used at the kinematic and dynamic levels. At the kinematic level, the adaptive compensator diminishes the unwholesome effects of unknown wheel slips. At the dynamic level, the adaptive compensator supplies the influential robustness to vanquish the uncertainties because of external disturbances, reconstruction error, etc. The stability of the whole control system is validated with Lyapunov theory. The comparative simulation results are shown to confirm the efficiency and validity of the control scheme.
  Keywords: RBF neural network; backstepping controller; adaptive compensator; unknown wheel slippage; mobile manipulator.
  
  
• Comparative study on mechanical dynamics of four lab-developed levitation prototypes  
  by Janardan Kundu, Vinod Kumar Yadav 
  Abstract: This paper highlights a broad investigation on system dynamics and its stability aspects of four different electromagnetic attraction type levitation prototypes. An exhaustive comparative study on levitation prototypes for a spherical object, two flat plates and a C-shaped plate has been discussed broadly. A spherical geometry has its advantages owing to the axis symmetry, whereas the plates have asymmetric symmetry. This geometry change brings a few significant challenges in design, modelling, controller design, fabrication and robustness of the set-up. Thus the study will help to develop more complex prototypes for real life applications e.g. MagLev (magnetic levitation) vehicle.
  Keywords: electromagnetic levitation; lead compensator; Windows comparator; frequency analysis.
  
  
• An adaptive distributed access control model for IoT and fog computing environments  
  by Lalla Amina, Charaf, Imam, Alihamidi, Anass, Deroussi, Abdessalam Ait Madi, Adnane Addaim, My El Hassan Charaf 
  Abstract: In this paper, we present a framework for handling access control in fog-based implementations. In order to accommodate the distributed aspect of the proposed fog-based architecture, we extend XACML-based control to a distributed adaptive XACML model (DA-XACML). As a main contribution, we define the layers of our architecture, the communication scheme between the different components of the architecture, and how to integrate DA-XACML to overcome the drawbacks of centralised access control solutions in the Core Cloud. Finally, we provide a simulation of our approach in an eHealth case study using the iFogsim2 simulator. Based on simulation results, the fog-based implementation not only yielded low energy use, network utilisation, delay, and policy execution cost, but also improved simulation time compared with cloud-based implementations.
  Keywords: fog computing; IoT; security and privacy; XACML; access control.
  
  
• Refined vector control structure and indirect MPPT for grid-connected DFIG-based wind energy conversion system, and appraisal on matrix converter interface  
  by Gayathri Kalimuthu, Jeevananthan Seenithangam 
  Abstract: The grid integration of wind energy conversion systems involving doubly fed induction generators is actualised by either the two-stage power converter (TSPC: back-to-back converter) or the single-stage power converter (SSPC: matrix converter). Though earlier vector control attempts have been successful in achieving independent active and reactive power control, they result in high ripples and poor power quality. This paper develops a refined vector control structure and incorporates a new indirect maximum power point tracking by exploiting the rule of thumb that for every wind speed, there is a unique optimal electromagnetic torque that extracts the maximum power. An arrived variant of the suggested control structure is suitable for the SSPC drive. The TSPC assumes a stator flux-oriented control (SFOC) for the rotor side converter and a voltage-oriented control for the grid side converter, while a single SFOC is employed in the SSPC. A real-time data driven simulation study on a 2 MW DFIG system demonstrates both disturbance rejection and tracking abilities.
  Keywords: doubly fed induction generator; single-stage power converter; two-stage power converter; Venturini modulation; wind energy conversion system; total harmonic distortion.
  
  
• Sliding-mode-based adaptive control of chaotic systems with time delays  
  by Ahmad Taher Azar  
  Abstract: Time-delay chaotic systems in nonlinear dynamical systems have recently received a lot of attention. In this paper, a synchronisation phenomenon is applied to synchronise four identical chaotic systems with time delays. For this purpose, a sliding-mode-based adaptive control is used, which has many applications owing to its ease of implementation, quick response, and good transient performance, as well as its insensitivity to parameter uncertainties and external disturbances compared with other control techniques. Only a few papers have used this controller to conduct combined synchronisation of time-delay chaotic systems. The necessary condition for the stability of an error dynamical system is derived using Lyapunov stability theory. To support the theoretical reasoning, numerical simulation is performed in Mathematica program. The complexity of this methodology contributes to increased communication security. To improve communication precision, the secret message can be partitioned into numerous components and loaded into two master schemes.
  Keywords: sliding-mode-based adaptive control; nonlinear dynamical systems; time-delay chaotic systems; Lyapunov stability.
  DOI: 10.1504/IJMIC.2023.10054105
   
  
• Modelling, bifurcation analysis, circuit design and FPGA-based implementation of a new chaotic jerk system exhibiting Hopf bifurcations  
  by Sundarapandian Vaidyanathan, Irene Moroz, Aceng Sambas, Daniel Clemente-Lopez, Jesus Manuel Munoz-Pacheco, Jose De Jesus Rangel-Magdaleno 
  Abstract: It is well-known that chaotic systems have several applications in scientific modelling and engineering fields such as encryption, cryptosystems, secure communication, etc. This work proposes a three-dimensional mechanical chaotic system with jerk dynamics. A detailed bifurcation analysis is conducted for the proposed chaotic system. It is shown that the proposed chaotic system has two equilibrium points which exhibit Hopf bifurcations. It is also shown that the proposed chaotic system depicts multistability and coexisting chaotic attractors. Using Multisim (Version 14), an electronic circuit is designed for the proposed mechanical chaotic system with jerk dynamics. As another engineering application, Field Programmable Gate Array (FPGA) design has been made for the proposed mechanical jerk chaotic system. Euler’s finite-difference method is used for our FPGA design. A hardware implementation of the FPGA-based design is performed in this work and experimental results are given in detail.
  Keywords: mechanical systems; jerk systems; chaos; chaotic systems; multi-stability; Hopf bifurcations; MultiSim design; circuit design; FPGA implementation; Euler's method.
  DOI: 10.1504/IJMIC.2023.10054238
   
  
• MATHEMATICAL MODEL FOR IMPACT OF AWARENESS ON COVID-19 VACCINATION AMONG THE YOUTH IN KENYA
  by Ancent Makau Kimulu, Abayomi Samuel OKE, Mark Kimathi, Charles Ndambuki Muli, Samuel Musili Mwalili, Winifred Nduku Mutuku 
  Abstract: Approximately 124 million cases of COVID-19 infections have been confirmed; with over 2.7 million deaths globally. Vaccines have been developed to control and contain the spread of COVID-19. However, due to the combined effects of misinformation and unawareness about the vaccines, 52% of the Kenyan youths (aged 18-35 years) are hesitantly waiting to see what happens to the vaccinated. As a result, this study models the effects of awareness on vaccine uptake among the youths in Kenya through the use of televisions, radios and social media platforms. The disease-free equilibrium (DFE) point and endemic equilibrium point of the model are obtained by setting the derivatives to zero. The reproduction number are determined by using the next-generation matrix. The condition for stability of the DFE is shown in relation to the reproduction number. The DFE was stable when the reproduction number R_0<1 and unstable when R_0>1. It is found that both means of awareness reduced the COVID-19 infections. A simultaneous use of the methods increases the number of Kenyan youths taking the COVID-19 vaccines and consequently, further reducing the number of infections among the youths.
  Keywords: COVID-19; next-generation matrix; Coronavirus; Awareness; vaccination; Youth
  
  
• Sliding mode switched tracking control of space robot manipulator  
  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 is 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.
  DOI: 10.1504/IJMIC.2023.10054956
   
  
• Joint variable and variable projection algorithms for separable nonlinear models using Aitken acceleration technique  
  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.
  DOI: 10.1504/IJMIC.2023.10054954
   
  
• Identification of the three-axis pedestal using Euler-Lagrange method using mathematical approach  
  by S. Mohammadreza Ebrahimi, Behrooz Rezaie, Mehdi Tavan 
  Abstract: One of the significant applications of pedestal is carrying and rotating antenna to precisely track satellites in space so that it can be possible to receive signals sent from the satellites. Three-axis pedestal is one of the best pedestals ever constructed and can be utilised 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.
  Keywords: mathematical model; mobile antenna; XYZ pedestal; modelling; validation; simulation.
  DOI: 10.1504/IJMIC.2023.10054119
   
  
• Stochastic pointwise second-order maximum principle for optimal continuous-singular control using variational approach  
  by Nour El Houda Abada, Mokhtar Hafayed 
  Abstract: In this paper, we establish the second-order necessary conditions for optimal continuous-singular stochastic control, where the system is governed by nonlinear controlled Itô stochastic differential equation. The control process has two components, the first being absolutely continuous and the second of bounded variation, non-decreasing continuous on the right with left limits. Pointwise second-order maximum principle in terms of the martingale with respect to the time variable is proved. The control domain is assumed to be convex. In this paper, the continuous control variable enters into both the drift and the diffusion terms of the control systems. Our result is proved by using variational techniques under some convexity conditions.
  Keywords: optimal control; stochastic continuous-singular control; pointwise second-order necessary conditions; variational method.
  DOI: 10.1504/IJMIC.2023.10054955
   
  
• Extended linear quadratic regulator control and its application in trajectory following control of autonomous vehicles  
  by Jianwei Wu, Lin Chen, Yang Zhou, Beibei Sun 
  Abstract: Due 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: extended linear quadratic regulator; ELQR; linear quadratic regulator; LQR; weight of input rate; genetic algorithm; algebraic Riccati equation.
  DOI: 10.1504/IJMIC.2023.10054959
   
  
• Identification of Hammerstein-Wiener time delay model based on approximate least absolute deviation  
  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 characteristics 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.
  DOI: 10.1504/IJMIC.2023.10054957
   
  
• Force/position control of constrained reconfigurable manipulators with sliding mode control based on adaptive neural network  
  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 bring 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 term included in the sliding mode is 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.
  DOI: 10.1504/IJMIC.2023.10054958
   
  

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

• Detection of coronary artery disease using machine learning algorithms  
  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.
  DOI: 10.1504/IJMIC.2022.10052707
   
  
• Optimisation of target coverage in wireless sensor networks using a learning automata approach  
  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  
  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.
  
  
• 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 modelling fault detection instead of modelling fault correction. We have proposed generalised 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.
  
  
• Classification of imbalanced hyperspectral images using ensembled kernel rotational forest  
  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  
  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.  
  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  
  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  
  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  
  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  
  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  
  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 demagnetisation 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 demagnetisation fault on them is analysed theoretically. A 1 kW, 12-pole prototype is studied, and the two-dimensional electromagnetic field and three-dimensional noise field models of the PMSG are established, and 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 demagnetisation fault conditions are simulated, and the simulation results show that the air gap flux density shows a large distortion under the demagnetisation fault conditions. 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; demagnetisation fault; noise field; electromagnetic field.
  
  
• 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 fires. 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 load were 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. Finally, a classifier for series arc fault diagnosis is designed using RF. The experimental data in this study were 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
  Keywords: arc fault detection; 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 to analyse 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 optimisation design of the bearing.
  Keywords: magnetic fluid bearing; parametric design; bearing capacity analysis; fluid-solid-thermal coupling; structural parameter optimisation.
  
  
• 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 optimisation 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 a lithium-ion battery is studied, and the online identification of model parameters by the 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 squares method to multiple innovations. Data were collected through HPPC cycle conditions and NEDC conditions experiments. The accuracy and convergence speed of the conventional RLS 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.
  
  
• A fast approximate entropy algorithm for heart rate variability analysis  
  by Haiping Yang, Lijuan Chou, Yongxin Chou, Jicheng Liu 
  Abstract: Approximate entropy is widely used in medical biological signal processing. However, due to the high complexity and time-consuming of approximate entropy calculation, it is generally only used for offline signal processing. In this study, the calculation process of approximate entropy is optimized. The goal is to shorten the running time of the algorithm without changing the approximate entropy value. The correctness and timeliness of the improved algorithm are verified by random number, and the improved algorithm is applied to HRV signal. Simulation results show that the improved algorithm can shorten the running time by 27-99 times, and the longer the cache length, the better the improvement effect. This makes it possible to process real-time biological signals with approximate entropy.
  Keywords: approximate entropy; microprocessor processing; ECG; HRV.
  
  
• An improved grid voltage observation method for grid-connected inverter  
  by Shuping Song, Xiaobo Sun, Zhihao Zhang, Huping Bao 
  Abstract: The voltage observation method via sliding mode observer (SMO) is widely used in the predictive control of grid-connected inverter (GCI) without AC voltage sensor. However, conventional methods not only need complex phase and amplitude compensation, but also are greatly affected by low-order harmonics of grid voltage. Therefore, a simple method of voltage phase and amplitude compensation is proposed, which is based on the conventional SMO. Besides, an improved phase-locked loop (PLL) is also adopted to reduce the interference of low-order harmonics in power grid. The improved PLL eliminates the interference of 5th and 7th harmonics and realizes the accurate observation of power grid frequency and angle. The effectiveness of the proposed method is verified by MATLAB/Simulink simulation.
  Keywords: grid voltage observation; predictive control; grid-connected inverter; PLL; SMO.
  
  
• Highly efficient on-line stochastic gradient and sliding window stochastic gradient signal modelling methods for multi-frequency signals  
  by Guanglei Song, Ling Xu 
  Abstract: This paper designs 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 modelling 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 optimisation loss function based on the cumulated dynamic measurements is proposed to present a highly efficient and high precision signal modelling methodology. Finally, the algorithm emulation is introduced to confirm the feature of the proposed signal modelling methodologies in improving the accuracy of parameter estimation.
  Keywords: signal modelling; parameter estimation; multi-frequency signal; gradient search.