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### International Journal of Modelling, Identification and Control

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 International Journal of Modelling, Identification and Control (63 papers in press) Regular Issues System identification of proportional solenoid valve dynamics   by Bakir Hajdarevic, Jacob Herrmann, Andrea Da Cruz, David Kaczka Abstract: As devices that convert electrical signals into mechanical forces and motions, proportional solenoid (PSOL) valves allow for modulation of flow or pressure in many industrial processes and medical applications. PSOL valves may also be incorporated into pneumatic or hydraulic systems using feedback loops, to allow for precise control of pressure or flow. Accordingly, the design process of any physical system using a PSOL mandates complete and accurate characterisation of its linearity and dynamic response. In this paper, we present a system identification technique for the characterisation of the linearity and dynamic response of a PSOL valve and its corresponding electronic control unit (ECU in the frequency-domain, using band-limited white noise as well as pseudo random non-sum non-difference (NSND) signals. The NSND waveforms consist of mutually prime frequencies over ranges from 0.195 to 37.4 Hz, to mitigate the effects of nonlinear distortions on the estimated linear system response. The parameters of several transfer function models, with varying numbers of poles and zeros, were simultaneously estimated from the voltage-flow frequency response of the system using a nonlinear gradient descent technique. The resulting candidate transfer function models were then assessed using the mean squared residual criterion (MSR) and the corrected Akaike Information Criterion (AICc). The MSR yielded a best fit transfer function consisting of ten poles and nine zeros, while the AICc yielded a simpler transfer function consisting of five poles and three zeros. Uncertainty analysis using a Monte Carlo simulation demonstrated fragile stability for the MSR-selected model with respect to varying parameter values within estimated uncertainties, yet a robust stability for the AICc-selected model. We conclude that our system identification technique for estimating linear transfer functions of ECU-PSOL systems will be useful for robust modelling, simulation, and design of pneumatic or hydraulic processes and applications. Keywords: proportional solenoid valve; mean squared residuals; Akaike information criterion; system identification; transfer functions; model optimisation; pneumatic systems. A real-time power-split strategy for a hybrid marine power plant using MPC   by Nikolaos Planakis, George Papalambrou, Nikolaos Kyrtatos Abstract: In this work, the problem of energy management strategies in hybrid diesel-electric marine propulsion systems is investigated with the implementation of Model Predictive Control (MPC). The system behaviour is described by models based on system identification from experimental data. These models are used for the design of predictive controllers. The controllers are designed to tackle with physical and operating constraints of the hybrid system. Different MPC designs are considered, in order to evaluate the capabilities of the proposed control concept. The controllers were successfully tested at the test bed of the laboratory, by evaluating diverse strategies for disturbance rejection, system stability, and operation of the plant within the operators desirable limits. Keywords: predictive control; hybrid marine propulsion; diesel-electric; data-based modelling; real-time control; power-split control. Oxygen therapy in chronic obstructive pulmonary disease: insight from convex optimisation   by Tanmay Pal, Pranab Kumar Dutta, Srinivasu Maka Abstract: Application of additional oxygen for managing acute exacerbation of Chronic Obstructive Pulmonary Disease (COPD) has an associated risk of oxygen toxicity. The aim of this work is to determine the appropriate level of oxygen for managing this condition using a mathematical model. In this approach, a noted respiratory regulation model is modified by impaired diffusion, dead space and variable blood flow to simulate COPD condition. This condition is manifested as variation of the equilibrium point of the model. As variation of these quantities happens over a long time, the steady-state model obtained from the dynamic model is used for further analysis. Simulation of the model shows that alveolar oxygen partial pressure reduces to 67.37 mmHg in COPD condition from 96.6 mmHg in normal condition. Similarly, alveolar carbon dioxide partial pressure increases to 54.73 mmHg in COPD condition from 40.03 mmHg in normal condition. Consequently, minute ventilation become 10.85 L/min in COPD condition, which is 97.63% higher than normal condition. Using the model, it is established that higher inspired oxygen increases alveolar oxygen, as well as alveolar carbon dioxide. It is also shown that higher inspired oxygen increases oxygen saturation and lowers the mismatch of ventilation-perfusion ratio. Using a quadratic combination of alveolar oxygen and carbon dioxide pressure, an objective function is proposed to calculate the optimal level of inspired oxygen, which is 186.84 mmHg. Results obtained from this analysis methodology are in agreement with clinical data. Keywords: mathematical model; respiratory regulation; COPD; oxygen saturation; ventilation-Perfusion ratio; convex optimisation; oxygen therapy. Neumann boundary geometric control of a fractional diffusion process   by Ahmed Maidi, Jean-Pierre Corriou Abstract: In this paper, a boundary controller is developed for the fractional diffusion equation in the framework of geometric control. The case of Neumann actuation with a spatial weighted average output is addressed. This non-collocated configuration is characterised by an infinite characteristic index. To overcome this difficulty, the notion of the extended operator is exploited to derive an equivalent distributed control problem. The equivalent model, obtained by the Laplace transform in space domain, is used both for controller design and stability analysis of the resulting closed-loop. Thus, based on the notion of the characteristic index, a state feedback control that enforces an output tracking is designed. Then, the exponential stability of the closed-loop is demonstrated based on the semigroup theory. The effectiveness of the developed controller is shown, through numerical simulation, in the case of a heated aluminium rod that exhibits an anomalous diffusion phenomenon. Keywords: distributed parameter system; spatial fractional partial differential equation; fractional diffusion equation; Neumann actuation; geometric control; characteristic index. A review on data-driven approaches for industrial process modelling   by Wei Guo, Tianhong Pan, Zhengming Li, Guoquan Li Abstract: Data-driven techniques in industrial processes have been continually improved during the past decades. However, there are many challenging issues in this field when the collected data presents different characteristics. In order to sketch the principle of different modelling methods under various working conditions, data-driven modelling methods from the perspectives of data structures and model structures are reviewed in this paper. Firstly, the data collection and preprocessing procedure are inspected. Then, popular methods from linear (including the multivariate linear regression, latent variable projection, etc.) and nonlinear methods (including artificial intelligence, Gaussian process regression, local model, etc.) are discussed. Finally, the model calibration strategies (including offset-based method, recursive method, moving window method) are also reviewed. The major purpose is to support the industrial process modelling for technical users by providing a set of data-driven methods. Keywords: data-driven modelling; industrial process; machine learning. Robust steering control for mobile-rack vehicles   by Boc Minh Hung, Sam-Sang You, Sang-Do Lee, Hwan-Seong Kim Abstract: To achieve precise navigation of a mobile rack vehicle (MRV), the lateral control system should have good adaptability to the perturbations of vehicle parameters under measurement noises and exogenous disturbances. The MRV for smart warehouse considered in this paper is a four-wheeled vehicle with autonomous motion. Vehicle lateral dynamics are affected by the variations of vehicle mass with loading, speed, and the cornering stiffness. Therefore, the active control system must guarantee stability and performance against uncertainties, over a wide range of parameter changes. This paper aims to develop a robust controller that stabilises the perturbed dynamic model while guaranteeing a specified performance. Moreover, the reduced-order controller developed has the ability to attenuate noises and disturbances in a cold environment without rail track. Finally, the dynamic performance of the robust controller is evaluated over a wide range of parameter variations while achieving positioning precision against various uncertainties. Keywords: mobile-rack vehicle; smart warehouse; vehicle dynamics; uncertainty; robust control. Observer-based output feedback integral terminal sliding mode control for nonlinear systems: multi-model approach   by Kaïs Hfaïedh, Karim Dahech, Tarak Damak Abstract: In this paper we propose an observer-based output feedback integral terminal sliding mode control for nonlinear systems. The state estimation problem is treated by using the Utkin observer under a multi-model structure. The design of the control law is based on the sliding mode theory. In fact, we propose two types of integral terminal sliding mode, which are sign integral and fraction integral. The objective of such observer-based control algorithms is to estimate the states of the system and to stabilise the output tracking error to zero. The stability proof is demonstrated by the Lyapunov approach. A numerical example of denitrification process is presented in order to validate the performances of the proposed control laws. Keywords: nonlinear systems; multi-model approach; integral terminal sliding mode control; state observer; output feedback control. Second-order terminal sliding mode control of five-phase IPMSM with super-twisting observer under demagnetisation fault   by Yaser Zafari, Sajjad Shoja Mahidabad Abstract: This paper deals with demagnetisation fault detection and toleration for five-phase interior permanent magnet synchronous motors through second-order sliding mode observer/controller. At the beginning, a super-twisting flux-linkage observer is proposed to cope with the chattering problem. This observer estimates the flux-linkage through the stator estimated currents. Further, a novel second-order terminal sliding mode controller is developed for mechanical speed control in the presence of demagnetisation fault. Finally, comparative simulations validate the feasibility and effectiveness of the proposed observer/controller for a five-phase interior permanent magnet synchronous motor. Keywords: five-phase IPMSM; super-twisting observer; demagnetisation fault; second-order sliding mode controller. Extended Kalman filter steady gain scheduling using k-means clustering   by Jun Chen Abstract: This paper studies the gain scheduling problem for the extended Kalman Filter (EKF). To save throughput, the steady gain is usually used for the Kalman filter, which can be obtained by solving a algebraic Riccati equation. In the context of EKF, the underlying model is nonlinear, and hence there is no universal steady state gain. In this paper, we propose a methodology to schedule gain for EKF. The idea is to offline linearise the nonlinear model at various operating points, and, for each of the linearised systems, to compute the steady state gain corresponding to the conventional Kalman filter. The operating space of the nonlinear model is then divided into multiple zones, through the k-means clustering algorithm, so that within zone, the steady state gains are close to each other. For real time filtering, the centroid of each zone is used as gain for the correction step, instead of computing the time-varying gain online, hence saving throughput. We apply the proposed methodology in a two-state nonlinear system, and show the throughput saving without impacting filtering performance. Keywords: extended Kalman filter; steady gain; k-means; gain scheduling. Active and reactive power control of a dual stator induction generator for wind energy conversion   by Fatma Lounas Abstract: This paper deals with the active and reactive power control of a Dual Stator Induction Generator (DSIG) based Wind Energy Conversion System (WECS). The DSIG is used instead of a Doubly Fed Induction Generator (DFIG) to avoid the main drawback of the slip-ring system. The DSIG has two three-phase windings in the stator; one is used as a Power Winding (PW) and the other as a Control Winding (CW). The aim of this article is to establish the relationships between the powers delivered from the power winding and the voltages applied at the control winding terminals, to build a simplified diagram of the DSIG which permits to synthesise easily PI regulators. The DSIG-based WECS is modelled and implemented under the Matlab-Simulink environment and a set of simulation tests for both hypo-synchronous and hyper-synchronous operating modes are performed to prove the feasibility and the validity of the developed control laws. Keywords: wind energy; MPPT; dual stator induction machine; doubly fed induction machine active power; reactive power; direct control; field oriented control; PI controller. Multi-source coordinated scheduling strategy of wind power-PV-CSP considering high energy load   by Xiaoying Zhang, Wei Xiong, Kun Wang, Xiaolan Wang, Wei Chen Abstract: With the rapid development of new energy power generation, there are many new challenges occurred in power system scheduling. This paper assesses wind power, photovoltaic (PV), and concentrating solar power (CSP) as a new energy hybrid generation mode, and proposes to use high-energy load as a schedulable resource to participate in the optimal scheduling strategy of new energy hybrid power generation. The optimal scheduling mode considers the randomness of wind power and PV, the controllability of CSP plant and the adjustability of high energy load. The multi-objective optimisation scheduling models are constructed with the minimum power output fluctuation of hybrid system and the maximum economic benefits of grid-connected. The multi-objective differential evolution algorithm based on non-dominated sorting (NSMODE) is used to optimise the solution; the high energy load is introduced to solve the problem of abandoned wind and light caused by the integration of new energy hybrid systems. Finally, the simulation analysis of the scheduling mode, optimisation algorithm and abandoned wind and light is carried out. The simulation results show that the participation of CSP plant and the participation of high energy load make the power fluctuation of the hybrid power generation system decrease and the economic benefits of grid-connected increases, the amount of abandoned wind and light is significantly reduced, and the use rate of new energy is improved. Keywords: new energy hybrid power generation; multi-objective optimization; high energy load; NSMODE; optimal scheduling. A hydraulic system based on the servo valve with dual input of machine and electricity   by Hao Yan, Bowen Jiang, Zheqing Zuo Abstract: The hydraulic system based on the servo valve with dual input of machine and electricity consists of the valve control system and the mechanical feedback device, which has a higher reliability. When the power of the system is cut off, the system can continue working until the actuator returns to the original position. This system is widely used in some occasions with higher reliability requirements. In this paper, the mathematical model of the system is established, where a certain transmission ratio between the actuator and the mechanical feedback is considered. Meanwhile, the key system parameters are analysed in order to reflect their influences on the system performance. It is obtained that the uncertainties of key parameters of the hydraulic amplifier have a certain impact on the dynamic and static characteristics of the system. Keywords: servo valve; dual input; mechanical feedback; dynamic and static characteristics. A divide-and-conquer based improved genetic algorithm for network selection in a heterogeneous wireless network   by Hui Sun, Chuang Yang, Rui Wang, Sabir Ghauri Abstract: Developing and using wireless networks is a trend to serve passengers in aircraft cabins. Cognitive radio technology can be used in the aircraft cabin wireless environment to solve the spectrum resource scarcity problem. Heterogeneous network access issue should be noticeable in cognitive radio wireless networks. In this paper, a improved genetic algorithm (GA) based on the divide-and-conquer is proposed to handle this problem. The proposed approach is compared with original GA, Particle Swarm Optimisation (PSO) algorithm and Tabu Search (TS) algorithm. The simulation results prove that the proposed method is valid. Keywords: aircraft cabin; wireless network; heterogeneous; divide-and-conquer. Modelling and sliding mode control of a wireless power transfer system for a battery electric vehicle charger   by Abdellah Lasioui, Hassan El Fadil, Aziz Rachid, Fatima-Zahra Belhaj, Fouad Giri Abstract: In this paper, a unidirectional wireless power transfer (WPT) system for a battery electric vehicle (BEV) charger is addressed. Firstly, a detailed analysis is given focusing on the following points: i) phase shift control technique, ii) reactive power compensation topologies, and iii) total harmonic distortion analysis. Secondly, a mathematical model is established for the studied system and its stability is discussed. It was found that the system presents an unstable behaviour when the voltage across the load is chosen as the system output. This nom minimum phase feature is dealt with using an indirect control strategy. Thirdly, based on the derived mathematical model, a nonlinear controller using the sliding mode control technique is developed. The control objectives are twofold: i) tight regulation of the output load voltage, and ii) asymptotic stability of the closed loop system. It is shown using theoretical analysis and simulation that the proposed controller meets all objectives. Keywords: electric vehicle; wireless power transfer; battery charger; phase shift control; sliding mode control. Kalman filtering linear quadratic regulator for artificial pancreas in type-I diabetes patient   by Akshaya Kumar Patra, Anuja Nanda Abstract: This manuscript presents a simulation model of the glucose metabolism process and design of a Kalman Filtering Linear Quadratic Regulator (KFLQR) to control the Blood Glucose (BG) concentration in Type-I Diabetes Mellitus (TIDM) patients. For designing of the KFLQR, a 9th order state-space model of the TIDM patient with Micro-Insulin Dispenser (MID) is considered. In this control strategy, the basic Linear Quadratic Regulator (LQR) is re-formulated with a state estimator based on the Kalman filtering approach for enhancement of control performance. The KFLQR is evaluated and compared with PID, LQR and pre-published control techniques suggested by different authors. The simulations are carried out through MATLAB/SIMULINK environment and the results indicate the better performance of the suggested algorithm to control the BG concentration within the normoglycaemic range in terms of accuracy, stability, quick damping and robustness. Keywords: type-I diabetes; MID; LQR; state estimator; KFLQR. Modelling and multi-loop selective control of industrial coal pulveriser   by Vini Dadiala, Jignesh Patel, Jayesh Barve Abstract: Coal-based power generation continues to be the key player in power generation. However, the efficiency of a thermal plant lies in the range of 30-40%, a sizably less value. Pulverisation of coal is an important but an energy-intensive process. Efficient control of the pulveriser can improve the efficiency of the overall plant. This paper discusses various computational results and their analysis for the case study of a coal pulveriser carried out at a thermal power plant in Gujarat, India. It proposes a more accurate mathematical model for a pulveriser with a static classifier and a 3PI (Proportional Integral) with selective control for improved performance. The proposed model is validated with real plant data from the 150 MW ESSAR thermal power plant, Gujarat. It is observed that the proposed model captures the system dynamics more effectively than the models existing in the literature. A 3PI with selective control strategy is proposed where the primary air flow is selected from the mill differential pressure loop and air-fuel ratio loop depending on operating conditions. It is observed that the new model with proposed control has better load disturbance rejection properties and is found to be more robust to parametric variations compared with the control strategy employed in the industry, wherein the mill differential pressure is controlled manually. Keywords: coal pulveriser; static classifier; coal mill modelling; parametric analysis; 3PI with selective control. XGBoost-PCA-BPNN prediction model and its application on predicting the effectiveness of non-surgical periodontal treatment   by Jinxiang Chen, Dong Shi, Jinqi Fan, Huanxin Meng, Jian Jiao, Ruifang Lu Abstract: An XGBoost-PCA-BPNN predication model is presented to classify and predict the objects based on the big data set with uncertain and coupling multi-dimensional characteristics, because the existing anyone single machine learning model cannot obtain the high prediction performances when it is applied to deal with the above problem. The XGBoost-PCA-BPNN model is applied to predict the effectiveness of non-surgical periodontal therapy (NSPT) for Chinese population with chronic periodontitis and the high prediction accuracy is obtained in this paper. Firstly, the advantages and the disadvantages of the existing machine learning approaches are analyzed. The XGBoost can handle\r\neffectively the coupling problems among multi-dimensional characteristics in big data sets. The PCA can reduce the dimension of inputs. BPNN can improve the accuracy of calculation, but the overfitting problems would be happened when it is used to handle the objects with multi-dimensional characteristics. The XGBoost-PCA-BPNN predication model is presented by combining XGBoost, PCA with BPNN in order to predict the objects with uncertain and coupling multi-dimensional characteristics. The model is verified by applying it to predict the effectiveness of NSTP for the big data set with 45,000 clinical chronic periodontitis sites. 30,000 sites are used as training samples and 15,000 sites are regard as testing data. Prediction results show that the Xgboost-PCA-BPNN model has higher predication accuracy, faster convergence speed and better stability than Logistic regression, Xgboost, Xgboost-Logistic regression. The $R^2$-score of the Xgboost-PCA-BPNN model is 0.943. In addition, it can be seen that the effectiveness of NSTP are mainly influenced by PD, BI, sites,age. Keywords: classification prediction; XGBoost; BPNN; non-surgical periodontal treatment; big data analysis; chronic periodontitis; effectiveness. Decoding fNIRS-based imagined movements associated with speed and force for a brain-computer interface   by Xinglong Geng, Zehan Li Abstract: Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive technology applied in brain-computer interface (BCI) systems. This study investigates fNIRS-based imagined hand-clenching tasks, indicating that the combinations of speed and force have distinct patterns that can be decoded to develop a BCI system. Twelve healthy participants were instructed to perform imagined left or right hand-clenching tasks; oxy-hemoglobin (HbO2) and deoxy-hemoglobin (Hb) concentrations were acquired from motor cortex using a multi-channel fNIRS system. A feature selection method based on mutual information was employed to select the optimal features for classification, and support vector machine (SVM) was used as a classifier, resulting in average accuracies of 84.9% and 86.1% for classifying left and right imagined movements, respectively. Compared with traditional fNIRS-BCI system, this study provides a possibility to generate a new control pattern for brain-controlled robots, e.g. speed or force control. There is also a potential application to combine fNIRS-BCI system with the exoskeleton to produce a complex rehabilitation strategy. Keywords: brain-computer interface; hand clenching; support vector machine. Linear discrete-time modelling and hybrid fault-tolerant controller design for complex systems with component and sensor faults   by Chunxiao He, Xisheng Li Abstract: A linear discrete-time model with the additive fault is constructed for the systems with component faults and sensor faults. A hybrid controller including the state feedback controller, the $H_\\infty$ filter and the fault-tolerant controller with $H_\\infty$ performance $\\gamma$ is designed in this paper. By using the Lyapunov function and linear matrix inequalities (LMI) approach, the theorem solving the designed controller gains is derived. The effectiveness of the presented approaches is verified by using them to control the Van der Pol circuit system with the ageing fault of components. Simulation results show that the designed controller can suppress the influence caused by components and sensor faults and stabilise the systems under meeting $H_\\infty$ index. Keywords: fault-tolerant controller; modelling; hybrid controller; $H_\\infty$ filter; additive faults; sensor faults; components. A survey of control strategies for grid connected wind energy conversion system based permanent magnet synchronous generator and fed by multi-level converters   by Youssef Errami, Abdellatif Obbadi, Smail Sahnoun Abstract: In this study, two control strategies for speed and power control of three-level neutral-point (3L-NPC) clamped back-to-back converters in Wind Energy Conversion System (WECS) with Permanent Magnet Synchronous Generator (PMSG) are proposed. The system consists of Generator Side Converters (GSCs) and Grid Side Converter (GSC) which share a common DC-link capacitor. The proposed control laws combine Sliding Mode Control (SMC) and Vector Oriented Control (VOC) to maximise the generated power from Wind Turbine Generators (WTGs). Considering the variation of wind speed, the GSC injects the generated power into the AC network, regulates DC-link voltage. Also, it is employed to achieve unity power factor. The GSCs are employed to achieve Maximum Power Point Tracking (MPPT). To validate the proposed approaches, simulations are carried out with MATLAB/Simulink software. The simulation results demonstrate a good performance in various scenarios. Keywords: wind electrical system; PMSG;3L-NPC; MPPT; SMC; VOC; grid. Input-to-state stability of systems with non-instantaneous impulses   by Cheng Liu, Zheng Fang, Jing Chen Abstract: In this paper, we investigate the input-to-state stability of systems with non-instantaneous impulses. By using the Lyapunov function with indefinite derivative and the average dwell time condition, we get a sufficient condition for the input-to-state stability of systems with non-instantaneous impulses, then we give an example in the end to show the efficiency of the theoretic result obtained in this paper. Keywords: impulsive systems; non-instantaneous impulses; input-to-state stability; average dwell time condition. Global stability and optimal control of melioidosis transmission model with hygiene care and treatment   by Ratchada Viriyapong, Sunisa Tavaen Abstract: A compartmental deterministic mathematical model for melioidosis transmission is proposed. It involves human and animal population and bacteria. We present two main equilibrium points (disease-free and endemic) with the analysis of their local stability. The basic reproduction number and its sensitivity index to the parameters in the model are calculated. Lyapunovs direct method is used to analyze the global stability of endemic equilibrium point. Further, by using Pontryagin's minimum principle, the optimal control problem is constructed with two controls, i.e. hygiene care and treatment controls for human population. Finally, the numerical simulations are established and our results show that a combination of the two controls gives more impact in reducing the numbers of infected human and bacteria than in reducing the number of infected animals. Because melioidosis prevalence is still increasing, more effort in sharing knowledge and controlling the spreading of this disease is still much required. Keywords: melioidosis; hygiene care; optimal control; Lyapunov’s direct method; Pontryagin's minimum principle. Nonlinear controller for MPPT based photovoltaic system under variable atmospheric conditions   by Fatima Ez-Zahra Lamzouri, El-Mahjoub Boufounas, Aumeur El Amrani Abstract: This paper depicts a robust controller design combining backstepping approach and sliding mode controller (BSMC) based maximum power point tracking (MPPT) for a photovoltaic (PV) system. The investigated PV system is based on a PV module as power source, a DCDC boost converter and a resistive load. A modified conventional perturb and observe (P&O) algorithm based MPPT control is designed, which presents good performances under constant atmospheric conditions. However, the solar radiation and cell temperature variations present a major effect on the PV output power. Thus, the proposed BSMC controller can allow to the PV system operate around the estimated MPPT under variable atmospheric conditions. Furthermore, the Lyapunov theory is used in order to demonstrate the stability of the PV system with BSMC controller. Moreover, the investigated control approach effectiveness is exhibited by comparing the developed BSMC controller, conventional sliding mode controller (SMC) and modified P&O algorithm. For the proposed BSMC approach, the obtained results with simulation illustrate good efficiency in terms of transition response, tracking error and fast response to atmospheric conditions variation. Keywords: photovoltaic system; maximum power point tracking; sliding mode control; backstepping approach; perturb and observe algorithm. A coevolutionary quantum krill herd algorithm for solving multi-objective optimization problems   by Zhe Liu, Shurong Li Abstract: Multi-objective optimisation (MOO) has always been a challenging problem that received considerable attention in practical engineering applications owing to the multicriteria objectives. This paper presents a coevolutionary quantum krill herd algorithm (CQKH) as a novel numerical method for solving MOO. The CQKH is a quantum-inspired evolutionary algorithm that improves the krill herd algorithm (KH) based on quantum representation and quantum rotation gate. As a result, CQKH has a stronger robustness and the capability of finding the optimal or near-optimal solution faster by fewer individuals. In addition, the CQKH adopts a coevolutionary technique named multiple populations for multiple objectives (MPMO) to obtain the whole Pareto optimal front. The computation results of CQKH on numerical tests with various characteristics demonstrate its effectiveness and superiority compared with some state-of-the-art algorithms. Keywords: multi-objective optimisation; coevolutionary quantum krill herd algorithm; multiple populations for multiple objectives; quantum representation; quantum rotation gate. Modelling, identification, implementation and MATLAB simulations of multi-input multi-output proportional integral-plus control strategies for a centrifugal chiller system   by Nicolae Tudoroiu, Mohammed Zaheeruddin, Roxana-Elena Tudoroiu Abstract: The objective of this paper is to investigate a new design and real-time implementation approach of a predictive proportional integral-plus (PIP) closed-loop control strategy for a centrifugal chiller HVAC system. As a case study, a dynamic model of a centrifugal chiller system developed in a previous study was considered. By using this analytical model as the plant, linear discrete-time polynomial multi-input multi-output (MIMO) autoregressive moving average models with exogenous input (ARMAX) were developed. The choice of ARMAX models is warranted since such models are simple in their structure and capture the dynamics of the centrifugal chiller plant which is of high complexity in terms of dimension and encountered nonlinearities. Fundamentally, these identified models use the least-squares estimation (LSE) method to evaluate the polynomials coefficients and model parameters implemented using specific tools provided by MATLABs system identification toolbox. The new modelling approach is beneficial for simulation purposes to prove the efficiency of the proposed closed-loop control strategy, the tracking performance, and its robustness to possible changes in the load disturbance and noise level of measurement sensors. Keywords: centrifugal chiller; MIMO ARMAX model; PI-Plus control; least-squares estimation; HVAC control systems. Coordination control and obstacle avoidance for a team of mobile robots in an unknown environment   by Mohammad Habibur Rahman, Sucheta Roy, M.D. AssadUz-Zaman Abstract: This paper presents a dual-level control structure for controlling a mobile robot and/or a team of mobile robots to navigate through an unknown (static or dynamic) environment. The higher-level controller operates in cooperation with robots state estimation and mapping algorithm, Extended Kalman Filter Simultaneous Localization and Mapping (EKF-SLAM), and the lower-level controller controls the motion of the robot when it encounters an obstacle, i.e., it reorients the robot to a predefined rebound angle and move it straight to maneuver around the obstacle until the robot is out of the obstacle range. The higher-level controller jumps in as soon as the robot is out of the obstacle range and moves the robot to the target destination. The obstacle avoidance technique involves a novel approach to calculate the rebound angle. Simulation results verified the effectiveness of the proposed control law. Further, a pilot experiment was carried out to validate the simulated results. The experimental results show that the proposed dual-level control structure can be effectively used to maneuver a mobile robot or a team of mobile robots to navigate through a dynamic environment. Keywords: EKF-SLAM; mobile robots; dual-level motion controller; obstacle avoidance. Population dispersal and optimal control of an SEIR epidemic model   by Soovoojeet Jana, Manotosh Mandal, Tapan Kumar Kar Abstract: This paper formulates and analyses an SEIR-type epidemic model with the effect of transport-related infection between two cities in the presence of treatment control. The dispersal of populations from one city to another city has an important impact on the dynamics of disease evolution. The proposed model system is studied in three different cases: (i) no population dispersal, (ii) dispersal for susceptible and exposed individuals only, and (iii) dispersal for all classes of the population. The most important parameter in an epidemic model is the basic reproduction number which is directly connected to the severity of the disease. It is calculated for all the different cases of the model system. It is found out that the equilibrium is disease-free if the basic reproduction is less than unity, otherwise the disease may remain in the system. In addition, the optimal control problem is constructed and solved analytically and numerically by considering the treatment control as a control variable. Further, we present a numerical simulation to confirm the analytical results. Finally, we show a comparison of the result of our predicted model with the real data of SARS (severe acute respiratory syndrome) outbreak in 2003 in Hongkong. Keywords: infectious disease; transport-related infection; basic reproduction number; optimal control. An improved ELECTRE-III method for recommending new energy vehicles with heterogeneous decision-making information   by Meng Fanyong, Ding Yuqing Abstract: New energy vehicle (NEV) is the development direction of automobile industry supported by the Chinese government. Different brands of NEVs have different performance, and it is not an easy thing to select the suitable NEVs. This paper first analyses the evaluation factors and establishes the index system. Then, a method for heterogeneous information transformation is introduced, and a method for determining the criteria weights based on linguistic variables is provided. After that, an improved ELECTRE-III method for recommending NEVs is proposed that can address the situations where there are heterogeneous decision-making information and unknown weighting information. To illustrate the practicality of the new method, a case study is provided. Meanwhile, comparison analysis with two existing methods is made. Keywords: multi-criteria decision making; new energy vehicle; ELECTRE-III method; heterogeneous information. Multiple U-model control of uncertain discrete-time nonlinear systems   by Weicun Zhang, Zhaolong Zhang, Qing Li, Zhuoer Xue Abstract: Based on U-model concept and multiple model methodology, this paper presents a weighted multiple U-model control scheme to address the control problem of some classes of discrete-time nonlinear systems with large parameter uncertainties including parameter jumps, which is a difficult problem without unified solution up to now. Simulation results on two types of nonlinear system with large parameter uncertainties verified the effectiveness of the proposed scheme. Keywords: U-model control; multiple model control; nonlinear system. Kinematic modelling and simulation of PID controlled SCARA robot with multiple tool end effectors   by M. Saravana Mohan, V. Anbumalar, S. Thirumalai Kumaran Abstract: The mechatronics approach is adopted to develop and control electromechanical systems such as robots. In this paper, the three-dimensional (3D) Computer Aided Drawing (CAD) model of a Selective Compliant Assembly Robot Arm (SCARA) robot with a multiple tool end effector (MTEE) is developed using SolidWorks software. A novel attempt of PID controller based simulation is carried out in SimMechanics simulation environment by MATLAB software. By linking CAD modelling, SolidWorks and MATLAB/SimMechanics software, the 3D CAD model of the SCARA is transformed into a series of blocks representing the multibody electromechanical system. The motion-sensing capability and the simulation modes of SimMechanics incorporated with PID controller are applied for positioning the end effector of the manipulator accurately. The results of the SimMechanics simulation presented in this paper infer that the position of the manipulator can be controlled precisely. Keywords: SCARA; multiple tool end effector; SolidWorks; SimMechanics; multibody simulation; PID controller. Robust finite-time sliding mode control of twin rotor MIMO system   by Kaushik Raj, Santosh Kumar Choudhary, Venkatesan Muthukumar Abstract: In this article, a robust finite-time sliding mode control of the Twin Rotor MIMO System (TRMS) is discussed. This helicopter laboratory model is highly nonlinear in characteristics and coupling dynamics between main and tail rotors. The main purpose of this paper is to investigate finite-time sliding mode control for pitch and yaw angles of TRMS, either for posture stabilisation or trajectory tracking. Moreover, these angles are used commonly to determine the hovering posture of a helicopter. The article first briefs the dynamical model of TRMS and then it adopts a finite-time sliding mode control technique to achieve the desired trajectory or posture stabilisation. Numerical simulation results are demonstrated and verify the effectiveness of the control technique. Keywords: twin rotor MIMO system; robust control; finite-time sliding mode control; nonlinear control systems; uncertain system; helicopter system. The condition number of the static gains matrix as a quality index in LPV IO MIMO multi-objective identification   by Oscar Daniel Chuk, Carlos Gustavo Rodríguez Medina, Enrique Antonio Núñez, Gustavo Scaglia Abstract: A quality index of linear multivariable models is presented in this article, with application to linear systems with variable parameters LPV systems. The index is based on the condition number of the static gains matrix of the process. An example of use in the identification by means of multiobjective optimisation of a non-linear process of two inputs and two outputs verifies the importance of the use of this index, in particular, if the identified model will be used for the synthesis of controllers. Keywords: condition number; modelling; multivariable systems; linear parameter varying systems; multi-objective optimisation. Self-Learning Salp Swarm Optimization Based Controller Design for Photovoltaic Reverse Osmosis Plant   by Naresh Patnana, S. Pattanaik, V.P. Singh, R. Kumar Abstract: In this work, a self-learning salp swarm optimisation (SLSSO) based controller design is proposed for a photovoltaic reverse osmosis (RO) desalination unit. The SLSSO algorithm is proposed in order to improve the performance of salp swarm optimisation. The photovoltaic RO model considered is basically an interacting two-input-two-output (TITO) system. The interacting TITO system is first converted into two non-interacting sub-systems by designing an appropriate decoupler. Then, two proportional-integral-derivative (PID) controllers are designed by minimising the integral-of-squared-error (ISE) of the respective non-interacting sub-systems. The ISE is designed in terms of alpha and beta parameters for ease of simulation. This designed ISE is minimised using the proposed SLSSO algorithm. For showing the efficacy of SLSSO-assisted PID controllers, other PID controllers are also obtained using some state-of-art optimisation algorithms. The results prove that SLSSO-assisted PID controllers outperform other PID controllers. Keywords: decoupler; desalination; photovoltaic RO system; salp swarm optimisation; tuning; water treatment. Minimal overshoot V-F control for islanded microgrids   by Ehab Bayoumi, Hisham Soliman, Mostafa Soliman Abstract: Islanded microgrids dynamics are greatly affected by the controllers gains and power-sharing parameters. This paper considers an islanded microgrid containing two distributed generation (DG) units. Each DG has its PWM inverter for three phases. Each inverter has two control loops in cascade. The inner loop is a current loop and the outer loop is a voltage loop. The controller of each loop is designed to provide good dynamic performance in terms of minimal percentage overshoot and overall system stability. Particle Swarm Optimisation (PSO) is used to design the current and voltage controllers to achieve the desired performance. The proposed controllers are compared with the conventional technique (Ziegler and Nichols) to show the excellence of the proposed technique. Different test scenarios, such as voltage and current tracking and load parameters variation, are used to examine the proposed design. Test results validate and endorse the effectiveness and superiority of the proposed controllers compared with the traditional one, in addition to enhancing the stability of the given microgrid system. Keywords: V-F control; microgrids; distributed generation; particle swarm optimisation. Application of ellipsoidal approximation into target tracking for multi UAVs formation cooperative detection   by Wang Jianhong, Meng He, Ricardo A. Ramirez-Mendoza Abstract: In this paper, the ground target positioning and tracking algorithm for cooperative detection of multi UAVs formation is studied. Then a real time and rapid algorithm is discussed based on UAV airborne electro-optical sensors. Because some information is embodied in the considered state, two state estimation problems for linear or nonlinear stochastic systems are considered under the conditions of statistical noise and unknown but bounded noise, respectively. First, in case of known probabilistic distribution of noise, the unscented Kalman filter algorithm is applied to estimate the unknown state for target tracking process. Secondly, to relax the strict condition on white noise in Kalman filtering theory, the problem of target tracking or state estimation is reduced to derive the inner and outer ellipsoidal approximations for the state in the case of unknown but bounded noise. The special case and more general case are all studied with the number of the ellipsoids, and some alternative forms are derived to obtain the approximate outer and inner ellipsoidal approximations. Finally, one simulation example confirms our theoretical results proposed in this paper. Keywords: multi UAVs formation; cooperative detection; target tracking; ellipsoidal approximation. Comparative studies between the Bayesian estimation and the maximum likelihood estimation of the parameter of the uniform distribution   by Bao Xu Abstract: The point estimation of the parameter ? of the uniform distribution U(0,?) is discussed. The general form of the Bayesian estimation of ? is investigated under the weighted square loss function in the framework of Bayesian statistics, and the precise form of the Bayesian estimation of ? is obtained, based on the given Pareto conjugate prior distribution. The comparisons between the Bayesian estimation obtained in the framework of Bayesian statistics and the maximum likelihood estimation obtained in the framework of classical statistics are studied from theory and simulation, respectively. Results show that the Bayesian estimation of ? under the weighted square loss function is smaller than the maximum likelihood estimation of ? in the framework of classical statistic in numerical value, and the Bayesian estimation that obtained is the maximum likelihood estimations of the corresponding functions of ?, respectively. Keywords: uniform distribution; Bayesian estimation; loss function; conjugate prior distribution; maximum likelihood estimation. A tracking method for inland river ships based on dual filters   by Lei Xiao, Minghai Xu, ZhongYi Hu Abstract: Recently, tracking algorithms based on correlation filter have achieved high performance in the video target tracking field. They have achieved good results in automobile and human tracking with long-term non-constrained video stream. However, when there is occlusion between ships, the tracking strategy of inland river CCTV (closed-circuit television) system is prone to drift. When the current video frame searches the moving ships exhaustively, it is found that the target ship and the background change greatly. This paper deeply analyses the problems existing in the correlation filter tracking system and the characteristics of the target scene, to deal with the problem of inland river ship tracking under severe occlusion. In this paper, we first apply variance filter to correlation filter tracking algorithm to significantly reduce candidate samples. Secondly, we propose an occlusion aware model to solve the problem of severe occlusion during target motion. Experimental results show that the proposed algorithm is more robust to occlusion than other algorithms. Keywords: correlation filter; variance filter; occlusion; ship tracking. Modelling and dynamic surface backstepping recursive sliding mode control for the speed and tension system of the reversible cold strip rolling mill   by Le Liu, Jia-Ping Qiang, Yi-Ming Fang Abstract: For the speed and tension system of the reversible cold strip rolling mill, a dynamic surface backstepping recursive sliding mode control (DSBRSMC) strategy is proposed based on the immersion and invariance (I&I) adaptive method and the nonlinear disturbance observer (NDO). First, by using the mechanism modelling method, a relatively complete mathematical model for the speed and tension system of the reversible cold strip rolling mill driven by alternating current (AC) asynchronous motors is established. Next, the I&I adaptive method is adopted to estimate the perturbation parameters of the system, and the NDO is developed to observe the system uncertainty. Again, controllers for the speed and tension system of the reversible cold strip rolling mill are presented by combining the backstepping control, the dynamic surface control, and the recursive sliding mode control. Theoretical analysis shows that the controller guarantees closed-loop systems stability in the Lyapunov sense. Finally, simulation research is carried out on the speed and tension system of a reversible cold strip rolling mill by using the actual data, and results show the validity of the proposed control strategy. Keywords: reversible cold strip rolling mill; alternating current asynchronous motor drive; immersion and invariance; nonlinear disturbance observer; dynamic surface backstepping control; recursive sliding mode control. Gap identification strategy for mobile robot navigation in static and dynamic environments   by Rekik Chokri Abstract: This paper presents a new strategy of mobile robot navigation inspired from Follow The Gap and Grouping Obstacles methods in static and dynamic environments. In this work, we have proposed a solution based on gap identification for the problem of obstacle avoidance. The mobile robot scans the surrounding through a laser sensor, then chooses the safest gap between the obstacles to reach the target. After that, the direction of the mobile robot is given by a fuzzy logic controller. This algorithm have shown its adaptability in cluttered environment and have produced satisfied results comparing to the methods suggested in previous works. On the other hand, we have added a new fuzzy logic controller in the case of dynamic obstacles to command the linear velocity of the robot. This approach was tested in some simulations, and have shown its efficiency in generating shorter and optimal pathes in a small time, with represents a great advantage. Keywords: mobile robot; willing gap; fuzzy controller; obstacle avoidance. Modified model-compensation ADRC controller and its application in PMSM current loop   by Yingning Gao, Xin Huo, Kemao Ma, Hui Zhao Abstract: Active disturbance rejection control (ADRC) is now widely applied in motor drives owing to its advantages like independence of system models and better disturbance rejection ability. For the current loop of PMSM, the uncertainties like model coupling and parameter variation can be estimated and compensated by ADRC. Considering that the total disturbance of current loop can be partially compensated by available plant characteristics, the idea of model compensation can be applied to the ADRC controller. However, the filter link in the current feedback loop is usually ignored in the conventional model compensation approach. Therefore, a modified model-compensation ADRC current control strategy is proposed with the filter link effect considered in this paper. Simulation and experimental results show that better current tracking performance is achieved by the proposed control strategy. Keywords: model-compensation ADRC; total disturbance; filter link; current loop. Under-actuated decoupling controller design and analysis based on U model   by Rui Wang, Yu Wang, Hui Sun Abstract: This paper proposes a controller design algorithm for the combination of under-actuated system control and U model control. First, the decoupling coordinate transformation of the under-actuated system greatly helps to reduce the complexity of the system. Second, inspired by the principles of U model, the control law of the under-actuated nonlinear system is established by using the linear pole placement method and satisfies the desired performance indexes. Furthermore, the method is able to be widely applied to different under-actuated nonlinear systems as well. Finally, MATLAB simulation verification confirms the feasibility of the algorithm. Keywords: under-actuated systems; U model; decoupling. Induction motor current ripple minimisation with PV-based SEPIC-cascaded inverter   by Walid Emar, Zayed Huneiti, Zakariya Al-Omari Abstract: In this study, an induction motor is supplied from a SEPIC converter that is extracting a direct current from a photovoltaic solar cell system. The DC output voltage of SEPIC is converted into a five-level AC output voltage using a cascaded H-bridge inverter. The five-level cascaded inverter with the SEPIC converter serves as a good interface utility between PV supply sources and the induction motor. This enables supplying the motor by a multi-level high-frequency output voltage and current. Various PWM modification techniques for the multi-level inverter are discussed in this study based on the multicarrier redistribution technique. The current and voltage total harmonic distortion (THD) level of the inverter is used to investigate the harmonic contents generated in the output waveform of the induction motor. Note that the total harmonic distortion (THD) generated at the output of the inverter and the input of the motor varies depending on the inverter topology, the levels of the multi-level inverter, and the modulation index. This is an important coefficient that affects the power losses and efficiency of the motor. To minimise the harmonic content of the induction motor and inverter, a new topology of multi-carrier PWM techniques, known as the Hybrid Trapezoidal Technique (HTrap), is used to control the switching of the five-level cascaded inverter (MLCI). This technique proved to have a reduced electromagnetic interference (EMI), as well as the lowest total harmonic distortion (THD), harmonic factor (HF), and crest factor (KF) without using inductors compared with other multicarrier PWM techniques. This method with the HTrap technique ensures maximum efficiency of the whole set (PV-based SEPIC-inverter-motor) and maximum power transfer under all operating conditions. This study also deals with the SEPIC converter performance within the region of discontinuity. The discontinuous modes, along with the voltage and current waveforms, are presented. Different technical parameters are also investigated and recorded. The main attention is focused on the analysis, experimental testing and simulation of the fundamental SEPIC converter, along with the five-level inverter and a three-phase induction motor. Simulations were performed using Simplorer 7 or Matlab and Excel to validate the concepts of SEPIC converter and multi-level cascaded inverter for grid-connected PV systems to supply AC motors. Keywords: induction motor control; SEPIC converter; harmonic content; five-level cascaded H-bridge three-phase inverter; hybrid trapezoidal carrier PWM technique; generic block diagram. A new family of 5-D, 6-D, 7-D and 8-D hyperchaotic systems from the 4-D hyperchaotic Vaidyanathan system, the dynamic analysis of the 8-D hyperchaotic system with six positive Lyapunov exponents and an application to secure communication design   by Khaled Benkouider, Toufik Bouden, Mustak E. Yalcin, Sundarapandian Vaidyanathan Abstract: This work reports a new family of 5-D, 6-D, 7-D and 8-D hyperchaotic systems derived successively from the 4-D hyperchaotic Vaidyanathan system (2018). The new 8-D hyperchaotic system possesses six positive Lyapunov exponents. We discuss the dynamic properties of the new 8-D hyperchaos system, describe its self-synchronisation and provide an application in secure communication. An equivalent electronic circuit of the 8-D hyperchaos is implemented using Multisim software to validate the physical feasibility of the system. As an application to secure communications, a new hyperchaotic transmission scheme is developed based on the drive-response synchronisation method and using all the 8-D hyperchaos signals generated by the proposed system. With its six positive Lyapunov exponents, the proposed 8-D hyperchaos system generates high complex behaviour. Thus, the new 8-D hyperchaos system can be deployed in many engineering applications, such as cryptosystems and secure communication. Keywords: chaos; hyperchaos; hyperchaotic systems; circuit design; synchronisation; secure communication. A new multistable hyperjerk dynamical system with self-excited chaotic attractor, its complete synchronisation via backstepping control, circuit simulation and FPGA implementation   by Sundarapandian Vaidyanathan, Esteban Tlelo-Cuautle, Aceng Sambas, Leutcho Gervais Dolvis, Omar Guillén-Fernández, Babatunde A. Idowu Abstract: In this work, we report a new 4-D chaotic hyperjerk system and present a detailed dynamic analysis of the new system with Lyapunov exponents, bifurcation plots, etc. We find that the new hyperjerk system exhibits multistability and coexisting chaotic attractors. The hyperjerk system has a unique saddle-focus rest point at the origin, which is unstable. This shows that the new chaos hyperjerk system has a self-excited chaotic attractor. As an application of backstepping control, we obtain new results for the global chaos complete synchronisation of a pair of chaotic hyperjerk systems. A circuit model using MultiSim of the new chaotic hyperjerk system is designed for applications in practice. Finally, an FPGA-based implementation of the new chaotic hyperjerk dynamical system is performed by applying two numerical methods, and their corresponding hardware resources are given. Keywords: chaos; chaotic systems; hyperjerk; backstepping control; synchronisation; circuit design; FPGA design. A hybrid CSS-GW algorithm for finding optimum location of multi semi-active MR dampers in building   by Farzad Raeesi, Hedayat Veladi, Bahman Farahmand Azar, Siamak Talatahari Abstract: Selecting a place where dampers should be installed has significant importance to achieve the best performance of them in reducing dynamic responses. Different methods can be used to find the optimum location of dampers in structures. One of the most widely used methods is the meta-heuristic algorithms. In this paper, charged system search (CSS) and grey wolf (GW) algorithms are hybridised as HCSS-GW, to improve the searching abilities in finding the optimum location of the multi-magnetorheological (MR) fluid dampers in structural buildings. In this proposed hybrid algorithm, the charged system search algorithm helps the grey wolf in generating the initial positions. In other words, the solutions of the CSS algorithm are regarded as the initial population of the GW, instead of generating initial random positions. To illuminate the validity of the HCSS-GW algorithm in solving other optimisation problems, some benchmark test functions are selected to compare the hybrid algorithm with both standard CSS and GW algorithms in evolving best solutions. The obtained results indicate that the HCSS-GW is highly robust and accurate in comparison with its constituent algorithms and can be used successfully in finding optimum locations of dampers in different buildings. Keywords: semi-active MR damper; optimisation; hybrid algorithm; optimum location. Incremental backstepping robust fault-tolerant control with improved IHSTD for RLVs   by Wu Liu, Yanli Du, Erwin Mooij, Haibing Lin Abstract: Aiming at unknown disturbances/uncertainties, partial effectiveness loss fault (PELF) and stuck failure (SF) of the actuator, a composite robust fault-tolerant control strategy based on incremental backstepping (IBS) is proposed for a reusable launch vehicle (RLV) during re-entry. By converting PELF into disturbances/uncertainties, this paper presents an incremental form of disturbance observer based on an improved inverse hyperbolic sine tracking differentiator (IHSTD) to compensate these interference terms originally ignored in the IBS design process. Furthermore, a failure symbol matrix is set to control the on-off states of the reaction control system of the RLV to make up for the missing torque of the actuator SF, which can strengthen the fault-tolerance capability of the control system. The simulation results show that the tracking effect of the proposed method on the attitude-angle commands is better than traditional backstepping with disturbance observer, and the presented control allocation strategy is capable of timely resolving the actuator SF problem to ensure stability of flight. Keywords: reusable launch vehicle; fault-tolerant control; incremental backstepping; tracking differentiator disturbance observer; reaction control system. Multipartite tracking consensus of linear MASs with arbitrarily projective parameters   by Liuxiao Guo, Jing Chen, Manfeng Hu, Zhengxian Jiang Abstract: This paper proposes distributed bipartite and multipartite tracking consensus for linear multiagent systems (MASs) with arbitrarily non-zero projective parameters in networks, which includes traditional consensus, bipartite consensus and group consensus as its special items. Based on the projective similarity transformation and Riccati inequality, novel types of protocol are designed to achieve bipartite and multipartite consensus exponentially without analysing the signed graph, as in most current literature on bipartite problems. For obtaining multipartite consensus involving less global information, the distributed protocols with adaptive tuning of the coupling strength are further adopted. Finally, the theoretical results are illustrated through two numerical simulation examples when linear systems are equilibrium point and periodic states. Keywords: multipartite consensus; multi-agent system; linear systems; projective parameters; adaptive control. Two redundant rule-based algorithms for time-delay nonlinear models: least squares iterative and particle swarm optimisation   by Yuelin Xu, Yingjiao Rong Abstract: Two redundant rule-based methods are developed for a time-delay nonlinear model in this paper. By using the redundant rule, the time-delay nonlinear model can be turned into a redundant model that contains some redundant terms. Then the least squares iterative and the particle swarm optimisation algorithms are applied to update the parameters and the corresponding time-delay. Compared with the redundant rule-based least squares iterative algorithm, the redundant rule-based particle swarm optimisation algorithm is more efficient for nonlinear models with complex structures. A simulation example shows that the proposed algorithms are effective. Keywords: nonlinear model; particle swarm optimisation algorithm; time-delay parameter estimation; redundant rule; least squares iterative. Modelling and compensation of temperature errors for articulated arm coordinate measuring machinesby Guanbin Gao, Wenjin Ma, JING NA, Fei Liu Abstract: Different from the traditional coordinate measuring machines which are generally used in constant temperature room, the articulated arm coordinate measuring machine (AACMM) is used in industrial sites. Hence, the temperature variation is an important factor affecting the accuracy of AACMMs, and thermal deformation error modeling and compensation play an important role in improving the measuring accuracy of AACMMs. This paper addresses the modeling and compensation of temperature errors in the AACMM. Firstly, a temperature field model of AACMMs is established by finite element analysis, based on which the influence of temperature change on single-point repeatability accuracy and spatial distance measuring accuracy for AACMMs are analyzed. The results of the analysis show that non-zero linear parameters of AACMMs are influenced by temperature variation greatly, while the angular parameters are almost unchanged. Furthermore, the spatial distance measuring accuracy of AACMMs is changed significantly rather than the repeatability when the temperature varies. Then, a temperature scaling method is proposed to improve the spatial distance measuring accuracy of AACMMs, and a linear regression temperature error compensation model is established under the simulation environment. Finally, the experimental research is carried out, and the results show that in the presence of temperature scaling method, the average absolute value of distance measuring accuracy is improved by 65.24%. Keywords: articulated arm coordinate measuring machine; repeatability; spatial distance measuring accuracy; error compensation; temperature compensation; finite element analysis. Robust control with an anti-windup technique based in relaxed LMI conditions for LTV systemby Rosana Rego, Marcus Costa Abstract: It is proposed, in this paper a new technique to address the anti-windup (AW) with model predictive control (MPC) scheme for linear time-varying (LTV) systems. The design problem of the anti-windup compensator is reduced to a linear matrix inequality optimization problem with relaxation. The main advantage of this new approach is the reduced conservativeness compared with other well-known anti-windup techniques and to prevent integration windup in MPC controllers when the actuators are saturated. The control with AW is applied in the polytope modeling of three-state switching cell (3SSC) DC-DC converter operating under saturation conditions in the control signal to avoid the overlapping e ect. The MPC with proposed anti-windup is compared with the MPC technique and with MPC-AW without relaxation. The MPC-AW with relaxation improve the performance when the converter operated in the saturated mode and allows the rational use of the converter, avoiding that the saturation damages its performance in a permanent regime. The simulation results validated the eciency of the proposed approach and showed that the relaxation approach not only allows working better with the polytope modeling but also improves the response under LTV disturbance. Keywords: Anti-windup; Model Predictive Control; Boost Convertere; Linear Time-Varying Systems; Linear Matrix Inequalities. Automatic regrouping of trajectories based on classification and regression tree   by Ying Zhang, Chenguang Yang Abstract: Decomposing complex tasks into simple sub-trajectories can greatly reduce the difficulty of modelling and generalisation. Using dynamic movement primitive (DMP) to generalise these sub-trajectories and combining the generalised sub-trajectories in a different order can generalise the original task to a new task, which greatly improves the generalisation ability of DMP. In previous work, we manually determined the recombination order of trajectories, but this method was inefficient and time-consuming. Here, we automate the procedure with the decision tree approach. First, we use some known decision results as prior information to generate decision trees. Then, we input the starting and ending coordinates of each sub-trajectory of the new task into the decision tree. The decision tree will make decisions based on the coordinate information and choose which kind of trajectory to generalise to realise the new task. Simulation results are used to verify the effectiveness of the proposed method. Keywords: dynamic movement primitive; trajectory segmentation; classification and regression tree. An Iterative Defogging Algorithm Based on Pixel-level Atmospheric Light Mapby Di Fan, Xiao Lu, Xiaoxin Liu, Wanda Chi, Shicai Liu Abstract: Most defogging algorithms often lead to the problem of sky oversaturation and non-sky brightness. In order to solve these problems, a dark channel iterative demisting algorithm based on pixel level atmospheric light map is proposed in this paper. Firstly, the algorithm in this paper obtains a pixel-level atmospheric light map based on the model of the relationship between fog density and depth of field. Secondly ,the algorithm uses an iterative defogging method to control the optimal defogging degree, thereby restoring high-quality defogging images. The experimental results show that the image obtained by the algorithm in this paper is not only high in definition but also real-time, and the problems of sky oversaturation and non-sky brightness are effectively solved. Keywords: image defogging; pixel-level; atmospheric light map; real-time; iterative defogging algorithm. RBF NN Observer based Adaptive Feedback Control for the ABS System Under Parametric Uncertainties and Modelling Errorsby Hamou AIT ABBAS, Abdelhamid RABHI, Mohamed BELKHEIRI Abstract: An anti-lock braking (ABS) scheme control is a relatively difficult task due to its highly uncertain nonlinear dynamics and time-varying nature of the parameters. According to the requirement that the braking process must be fast and robust, we contribute in the current paper to extend the universal function approximation property of the radial basis function (RBF) neural network (NN) to design both : a) adaptive NN observer to estimate derivatives of the tracking error dynamics since the availability of the ABS model is not always practical, b) and robust NN output feedback controller that will overcomes successfully parametric variations and uncertainties in order to address the tracking probem with bounded errors. Notice that the feedback linearization control is introduced to linearize the ABS nonlinear system, and the dynamic compensator is involved to stabilize. The estimated states are used as inputs to the NN and in the adaptation laws as an error signal. The stability of the proposed controller in the sense of Lyapunov guarantees boundedness of both tracking errors, and estimating errors of the closed-loop system. Simulations of the proposed control algorithm based adaptive RBFNN observer are conducted then compared to the Bang-bang controller to demonstrate its practical potential. Furthermore, both feasibility and efficiency have been successfully confirmed through robustness test. Keywords: Antilock braking system; Parametric Variations; Unmodelled Dynamics; Radial Basis Function Neural network; Adaptive Observer; Comparative Study; Robustness Test. Special Issue on: ICMIC 2019 Mathematical Modelling and Advanced Control Approaches of Nonlinear Complex Dynamics Estimation of inhalation exposure to metals among welders of a steel company using MEASE model: as a screening tool for estimates of occupational exposure   by Sara Karimi Zeverdegani, Younes Mehrifar, Masoud Rismanchian Abstract: Estimation and assessment of substance exposure for metals is a tool to estimate inhalation exposures for metal substances. The aim of the present study was estimation of exposure to welding fumes using MEASE model, and also comparison of the estimated data with exposure levels by NIOSH 7300 in different welding processes. The metal fumes including Cu, Fe, Ca, Al, Mg, Mn, K and Na in the MIG, MAG and SMAW processes were measured according to NIOSH 7300. The occupational exposure estimation to the metal fumes was performed by MEASE model. There was fair agreement between measured and estimated values in terms of different metal fumes and welding processes(r = 0.131 to 0.933).A significant strong correlation was found between measured and estimated levels for Mg(r = 0.933;P = 0.001), Ca(r = 0.896; P = 0.001), K(r = 0.805; P = 0.001), Na(r = 0.716; P = 0.001), and Al (r = 0.756; P = 0.032). There was a significant strong correlation between measured and estimated values for SMAW(r = 0.708; P = 0.003) and MIG (r = 0.635; P = 0.036). The authors expect that the MEASE model cannot be wholly successfully applied for semiquantitative inhalation exposure assessment in occupational health surveys. Keywords: estimation; inhalation exposure; MEASE model ; metal fumes; welding processes. Development of human lower extremity kinematic and dynamic models for exoskeleton robot-based physical therapy   by S.K. Hasan Abstract: The World Health Organization reports that approximately one billion people are disabled in the world. Rehabilitation programs help promote functional recovery in disabled individuals. Exoskeleton robot-based physical therapy is an appealing solution for a large number of disabled people. Mechanical design, modelling, and control of exoskeleton robots require anthropometric data. A majority of anthropometrical data is not readily available from a single source. Furthermore, seven degrees of freedom human lower extremity kinematic and dynamic models are also not available. This paper presents dynamic modeling and simulation of the human lower extremity. The Lagrange energy method is used for developing a lower extremity dynamic model. The dynamic simulation utilizes a Computed torque controller. A Sliding mode controller is also developed for practical applications. The Sliding mode controller is a robust control scheme, which works efficiently in the presence of disturbances and parameter variations. Human lower extremity degrees of freedom, range of motion of various joints are integrated into the proposed model. Simulation results show the performance of the controller, joint torque, and power requirements for tracking a specified trajectory. The proposed model can be used as a reference to develop and verify a human lower extremity dynamic model. Since the human lower extremity exoskeleton robot should possess a similar dynamical behavior, the proposed model can easily produce the dynamic model of lower extremity exoskeleton robot by considering the masses, inertial properties and joint frictional forces of links in the exoskeleton robot. Because of its performance in the presence of simulated disturbances and parameter variations, it is seen that the sliding mode controller is an effective choice for controlling a real robot. Keywords: physiotherapy; exoskeleton robot; lower extremity anthropometric parameters; sliding mode controller; lower extremity kinematic and dynamic model. Identification of a deterministic Wiener system based on input least squares algorithm and direct residual method   by Shaoxue Jing Abstract: The Wiener system is a type of block-oriented system that consists of a linear model followed in series with a static nonlinear element. In this work, two novel identification methods are proposed to estimate the order and parameters of a class of Wiener system whose linear part is a finite impulse response function and whose nonlinear inverse function is a polynomial. First, a direct order identification method using the input-output data rather than an unknown intermediate variable is designed to estimate the order of the linear part. The method decreases the computational cost and improves the accuracy of order estimation, because it doesn't require calculating the intermediate variable. Second, an identification algorithm minimising the input prediction error is developed to obtain parameters of the Wiener system. Third, a numerical simulation and a case study verify the proposed algorithm. The proposed methods, with a little modification, can be applied to identify other block-oriented systems. Keywords: order estimation; parameter estimation; Wiener system; residual analysis. Robust pole-placer power system stabilisers design via complex Kharitonovs theorem   by Mohamed Ayman, Mahmoud Soilman Abstract: In this paper, synthesising robust three-parameters power system stabilisers (PSSs) having a common form of? (x?_1+x_2 s)/(1+x_3 s) is presented. Graphical characterisation of the set of stabilising PSSs is carried out using D-decomposition whereas the controller-parameter space is subdivided into root-invariant regions. The dynamic model of single-machine infinite-bus system (SMIB) is considered to accomplish the design. Rather than Hurwitz stability, D-decomposition is extended to consider D-stability, where D refers to a pre-specified damping cone in the open left half of the complex plane to enhance time-domain specifications. Pole clustering in the damping cone is inferred by enforcing Hurwitz stability of a complex polynomial accounting for the geometry of such a cone. Parametric uncertainties of the model imposed by continuous variation in load patterns is captured by an interval polynomial. As a result, computing the set of all robust D-stabilising PSSs calls for Hurwitz stability of a complex interval polynomial. The latter is tackled by a complex version of Kharitonovs theorem. A less-conservative and computationally effective approach based on only two extreme plants is concluded from the geometry of the stability region in the controller parameter plane. Simulation results affirm the robust stability and performance of the proposed PSSs over wide range of operating points. Keywords: PSS design; robust control; D-decomposition; interval polynomial; Kharitonov’s theorem; complex polynomials. Model-predictive-control complex-path tracking for self-driving cars   by Wael Farag Abstract: In this paper, a comprehensive Model-Predictive-Control (MPC) controller that enables effective complex track manoeuvring for Self-Driving Cars (SDC) is proposed. The paper presents the full design details and the implementation stages of the proposed SDC-MPC. The controller receives several input signals, such as an accurate car position measurement from the localisation module of the SDC measured in global map coordinates, the instantaneous vehicle speed, and the reference trajectory from the path planner of the SDC. Then, the SDC-MPC generates a steering (angle) command to the SDC in addition to a throttle (speed/brake) command. The proposed cost function of the SDC-MPC (which is one of the main contributions of this paper) is very comprehensive and is composed of several terms. Each term has its own sub-objective that contributes to the overall optimization problem. The main goal is to find a solution that can satisfy the purposes of these terms according to their weights (contribution) in the combined objective (cost) function. Extensive simulation studies in complex tracks with many sharp turns have been carried out to evaluate the performance of the proposed controller at different speeds. The analysis shows that the proposed controller with its tuning technique outperforms the other classical ones like PID. The usefulness and the shortcomings of the proposed controller are also discussed in detail. Keywords: MPC control; self-driving car; autonomous driving; MPC tuning. Special Issue on: Robotic Intelligent Control Systems Backstepping controller design with a quadratic error for a double inverted pendulum   by Boutaina Elkinany, Mohammed Alfidi, Soukaina Krafes, Zakaria Chalh Abstract: This study aims at presenting a conceptualisation of a double inverted pendulum system based on modelling, and controlling this model by applying only a single torque in the upper part instead of the lower part of the double inverted pendulum. Nonlinear dynamic equations were analysed using the Lagrangian dynamic formulation, and the graphical presentation of the system has been achieved through applying the bond graphs approach. The double inverted pendulum representation was incarnated using the 20-Sim software to build the system bond graphs in order to check on the motion. To achieve the system's stability, only one command was applied on the upper part. Most importantly, a control approach combining the backstepping method with the quadratic error was designed taking into consideration all nonlinearities that cannot be deleted. Indeed, the simulation results armed the effectiveness of the backstepping controller with the quadratic error and a good response of the system's flexibility was ensured in the sense that it can be adjusted from the initial position to the equilibrium position. Keywords: double inverted pendulum; backstepping controller; quadratic error; stability; Lyapunov. A novel sliding mode composite control design for fast time performance of quadrotor UAV   by Sudhir Nadda Abstract: The dynamical model of quadrotor unmanned aerial vehicle (UAV) is nonlinear, multivariable and unstable. Lots of control methods are available, but the existing controls are not sufficient to achieve stability and accuracy in shorter time. This study presents a composite control approach to perform the attitude and position tracking of a quadrotor UAV. The proposed control scheme has two steps. In the first step, the dynamical model is decomposed into two parts, i.e. a fully actuated subsystem and an underactuated subsystem. In the second step, the sliding mode control has been used to control the underactuated subsystem and terminal sliding mode control has been exploited to control the fully actuated subsystem. The terminal sliding mode control with nonlinear sliding surface for high accuracy tracking performance is applied to the fully actuated subsystem, and sliding mode control with linear sliding surface is applied to the underactuated subsystem. The application of terminal sliding mode provides the guarantee of finite time convergence. The stability of the system has been ensured by obtaining the condition on control parameter using Lyapunov criterion. The performance of the proposed control was evaluated and it has been found that there is substantive improvement over the performance of the conventional one. Keywords: quadrotor; terminal sliding mode control; sliding mode control; composite control. Improving the performance of medical robotic system using H? loop shaping robust controller   by Shahad Sami Ali, Safanah Mudheher Raafat, Ayman AL-KHAZRAJI Abstract: In order to solve the relevant and yet open problem of precise tracking, the current research synthesises a robust controller via H? loop shaping for a human swing lower limb system. The human walking is naturally difficult with particularly nonlinear dynamics. It is interpreted as pendulum links that stand for human thigh and shank. Actually, a reliable and efficient controller for a human swing leg robot system faces serious problems due to weight variations, modelling uncertainties and different disturbing effects. The current work takes into account these constraints through designing a robust controller based on loop-shaping framework. This provides an appropriate approach to compromise the robustness and precise tracking for a pre-specified variation of weight factors, and uncertainties in the dynamical models. In order to obtain the whole gesture of all muscles, two necessary control actions were developed and applied at the joints. Moreover, the paper demonstrates rigorously the robust stability and tracking. The obtained results from numerical examples confirm the effectiveness of the proposed controller as well as its remarkable simplicity. Keywords: robotic system; H? loop shaping; swing leg system; pendulum links; biped robot; robust control. Fractal, chaos and neural networks in path generation of a mobile robot   by Salah Nasr, Kais Bouallegue, Hassen Mekki Abstract: In this paper, we present different approaches using fractal, chaos and neural networks to generate the path of a mobile robot with obstacle avoidance. Firstly, the fractal process, which is inspired from Julia set, is applied to control the robot trajectory by designing fractal processes in cascade. This method increases the dynamic of robot trajectory with obstacle avoidance. Secondly, we believe that the edge of fractal approach is the chaotic system, so we use Lorenz chaotic attractor to control the same robot by combining the control parameter and the sine function in the second equation of the chaotic system. Thirdly, we use neural networks characterised by a variable structure model of neurons to control a robot. Numerical simulations are performed to verify the accuracy for each proposed approach. Keywords: mobile robot; chaos; fractal; neural networks; path planning; obstacle avoidance. Hybrid ANFIS-ant colony based optimisation for UAV trajectory tracking control   by Boumediene Selma, Samira Chouraqui, Hassane Abouaïssa Abstract: Development of Unmanned Aerial Vehicles (UAVs) has become one of the most important research areas in the field of autonomous aeronautical control. This paper proposes an optimal intelligent controller based on Adaptive-Network-based Fuzzy Inference System (ANFIS) and Ant Colony Optimisation (ACO) algorithm to govern the behaviour of a three degree of freedom quadrotor unmanned aerial vehicle. The quadrotor was chosen owing to its simple mechanical structure; nevertheless, these types of aircraft are highly nonlinear. Intelligent control such as fuzzy logic is a suitable choice for controlling nonlinear systems. The ANFIS controller is used to reproduce the desired trajectory of the quadrotor in a 2D vertical plane, and the ACO algorithm aims to facilitate convergence to the ANFIS optimal parameters in order to reduce learning errors and improve the quality of the controller. To evaluate the performance of the proposed ACO-tuned ANFIS controller, a comparison between the proposed ANFIS-ACO controller and other controllers, such as ANFIS only and Proportional-Integral-Derivative (PID) controllers, is illustrated using the same system. As expected, the hybrid ANFIS-ACO controller gives more satisfactory results than the other methods already developed in the same study. Keywords: unmanned aerial vehicle; optimal control; adaptive neuro-fuzzy inference system; ant colony algorithm.