# Forthcoming articles

International Journal of Modelling, Identification and Control

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 International Journal of Modelling, Identification and Control (66 papers in press)  Regular Issues  Designing Route Guidance Strategy with Travellers Stochastic Compliance: A Bi-level Optimal Control Procedureby Wei-li Sun, Ling-long Hu, Ping Li, Hui Wang  Keywords: . Sparse parameter estimation of LTI models with l^p sparsity using genetic algorithm   by Vikram Saini, Lillie Dewan Abstract: Sparse optimisation for the identification of parametric linear model structures is equivalent to the estimation of the parameter vector. After relaxing the assumption on the order of the system, sparse optimisation techniques can be used to find the optimal model. This paper proposes an optimisation method to find the sparse parameter estimates. For this purpose, l^p norm (0 Keywords: sparse optimisation; genetic algorithm; l^p sparsity measure; simulation error model. Identification of a magnetic levitator using NARX-OBF models and genetic algorithm   by Elder Oroski, Rafael Holdorf, Adolfo Bauchsspies Abstract: The Volterra models using Orthonormal Basis Functions (OBF) are very common in the system identification literature. These models are called Volterra-OBF and they only use polynomial operations with the filtered input signals to capture the behaviour of dynamic systems. The extension of this idea to the filtered output, combined with the filtered input signals, leads to the NARX-OBF (Nonlinear Auto Regressive with eXogenous Input - Orthonormal Basis Function) models. Within this context, the goal of this paper is to identify a nonlinear system with a NARX-OBF model and compare its results with the one obtained using a Volterra-OBF model. In order to determine the model parameters, some heuristic optimization methods are presented. The identification of a magnetic levitator is presented in order to exemplify the use of these models. Regarding the comparison between NARX-OBF and Volterra-OBF, in nonlinear system identification, one can conclude that NARX-OBF models have reached smaller Mean Square Error (MSE) in tested cases. Keywords: system identification; orthonormal basis functions; genetic algorithm; Volterra and NARX models. A new adaptive sliding mode control of nonlinear systems using Volterra series: application to hydraulic system   by Anouar Benamor, Hassani Messaoud Abstract: In this paper, we propose a new adaptive sliding mode control for nonlinear systems that are affine with respect to control, and where the free term of state representation is assumed to be unknown and modelled using the Volterra series. The proposed control law depends on the estimated parameters of Volterra series. The Lyapunov function was defined based on the sliding surface and the errors between the Volterra model parameters and their estimated values. The Lyapunov function is defined as positive and decreasing, which shows the systems studied. An example of simulation and a validation on a real system are given at the end of this paper to show the effectiveness of this approach. Keywords: sliding mode; nonlinear; Lyapunov function; Volterra series. An optimal inventory model with partial backorders and diminishing demand rate   by Cheng-Hsiung Lee, Hung-Lin Lai, Jinshyang Roan Abstract: Most inventory models discuss two extreme situations with respect to the demand in stock-out period. In this research, the demand rate within stock-out period is assumed as a diminishing function of backorders. Shortage of inventory will lead to the opportunity cost of lost sales. This research considers backorders and lost sales to formulate an inventory model with partial backorders. The objective of the inventory model is to determine the time scales of inventory depletion and stock-out periods in order to minimise total relevant cost. An efficient algorithm is developed to find the optimal solution. Finally, a sensitivity analysis is performed to study the effects of the model parameters on the optimal solution. This research apparently makes an improvement compared with the previous works, and further fits the requirements of practical environment. Keywords: inventory model; partial backorders; diminishing demand rate; stock-out period. Robust Q-parameterisation control for nonlinear magnetic bearing systems with imbalance based on TSK fuzzy model   by Mohamed Fekry, Abdelfatah M. Mohamed, Mohamed Fanni Abstract: This paper presents a methodology for designing a robust gain scheduled Takagi-Sugeno-Kang (TSK) fuzzy Q-parameterisation controller for nonlinear magnetic bearing systems subjected to imbalanced sinusoidal disturbance. First, the mathematical model of nonlinear magnetic bearing is presented. Second, a set of Q-parameterisation observer based stabilising controllers is obtained, based on linearisation of the nonlinear system at different operating points. Third, the structure that combines the Q-parameterisation observer based controller (OBC) with TSK fuzzy modelling to overcome the model nonlinearity and expand the operating envelop is explained. Fourth, the proposed controller is applied to a nonlinear magnetic bearing system. Finally, the simulation results are presented. The results clearly show that the proposed controller is able to merge the intelligence of fuzzy systems with robustness of Q-parameterisation control to extend the operating range up to more than 80% of the gap length and reject imbalanced sinusoidal disturbances at different operating speeds. Keywords: distribution control; robust control; robust stability; fuzzy supervision; Q-parameterisation; magnetic bearings. Euresis-Filter: a robust multiple-model FDI technique for small satellite thruster faults   by Nikolaos Tantouris, Kleanthis Dellios Abstract: Fault Detection and Isolation (FDI) techniques are properties of critical importance for any aerospace missions where autonomy and fault identification (malfunction diagnosis) must be present all the time. The present work provides an extended presentation of the Euresis-filter, a multiple model-based FDI technique amenable to the small satellite thruster faults. The main scope of the proposed multiple model-based FDI function is to maintain the spacecraft (S/C) operational and safe (healthy status) as required by the mission, including the analysis, development and design of the Euresis-filter to the LPF model and Monte Carlo simulation results related to thruster faults. Results reveal that the Euresis-filter can serve as an advanced FDI and fault tolerance control technique in terms of reliability, safety and mission success when compared with classical FDI/FDIR approaches. Keywords: satellite; autonomy; thrusters; fault detection and isolation; control; multiple model; robustness; Euresis-filter. Reliability and performance improvement of double-fed induction generator-based wind energy conversion system   by Khaled Benyahia Abstract: The aim of this paper is to present a new coordination control between active crowbar and PV-STATCOM to enhance the performance and the reliability of grid connected double-fed induction generator (DFIG) based wind farm under grid disturbance. A new technique to detect the fault is also presented. It is based on monitoring the rotor voltages and currents of the DFIG by using symmetrical components approach. A modified control scheme of solar farm converter is adopted to operate as STATCOM in the presence of disturbance. The proposed control scheme is simulated under MATLAB/Simulink platform to verify their efficiency. Keywords: double-fed induction generator; wind power plants; voltage dip; crowbar protection; low voltage ride through; STATCOM; photovoltaic system; system stability. A sentiment analysis approach based on exploiting Chinese linguistic features and classification   by Kai Gao, Shu Su, Dan-yang Li, Shan-shan Zhang, Jiu-shuo Wang Abstract: This paper proposes a novel approach to exploiting linguistic features and SVMperf algorithm based semantic classification, and this approach is applied into sentiment analysis. It uses the dependency relationship to do the linguistic feature extraction. This paper adopts χ2 (chi-square) and Pointwise Mutual Information (PMI) metrics for feature selection. Furthermore, as for the approach on sentiment analysis, this paper uses the SVMperf algorithm to implement the alternative structural formulation of the SVM optimisation problem for classification. E-commerce datasets are used to evaluate the experiment performance. Experiment results show the feasibility of the approach. Existing problems and further works are also presented. Keywords: sentiment analysis; linguistic feature; SVMperf; classification. Output feedback polytopic LPV Tube-RMPC control for air-breathing hypersonic vehicles   by Chaofang Hu Abstract: This paper proposes an output feedback tube-based robust model predictive control (Tube-RMPC) scheme for air-breathing hypersonic vehicles. Firstly, the polytopic linear parameter varying(LPV) model is established by Jacobian linearisation and tensor-product(T-P) modelling for the longitudinal dynamics. Secondly, a robust polytopic state observer is designed to estimate the attack angle, pitch angle and pitch rate by using the limited information of altitude and velocity. Then, the Tube-RMPC controller satisfying all vertices of polytopic LPV model is presented. Wherein, estimation error and control error are bounded by two robust positively invariant sets, respectively. The Tube-RMPC controller ensures that the actual states lie in a tube centred with the nominal states. The input constraints of original system are guaranteed by employing tighter constraints for nominal system. Finally, simulation results show the feasibility and effectiveness of the proposed method for hypersonic vehicles. Keywords: robust model predictive control; output feedback; tube; air-breathing hypersonic vehicle; polytopic LPV model. Multiple model approach for nonlinear system identification with mixed-Gaussian weighting functions   by Lei Chen, Yongsheng Ding Abstract: Multiple modelling strategies have been developed for industrial processes with multiple operating conditions. However, in most of the existing work, the Gaussian weighting functions are considered to combine all local models by assuming the distance between the adjacent operating points is not changed significantly, which is not appropriate for the transit data with significant changes. In this paper, a multiple model approach with the mixed-Gaussian weighting functions is proposed for nonlinear process identification. The mixed-Gaussian weighting functions as the probability distributions are assigned to each local model. Three different mixture weights are introduced: the mixture weights are pre-determined; the mixture weights are an unknown matrix; and the mixture weights follow Gaussian distribution. Under the framework of the expectation-maximisation (EM) algorithm, the parameters of local ARX models as well as those of the mixed-Gaussian weighting functions are estimated simultaneously. To illustrate the effectiveness of the proposed approach, a numerical example and a distillation column example are considered. Furthermore, an experimental study on a pilot-scale hybrid tank system is also provided to highlight the practical utility. The validation results demonstrate the advantages of the proposed approach. Keywords: mixed-Gaussian weighting functions; nonlinear process identification; multiple models; expectation maximisation algorithm. Dynamic coupling analysis for the design of hybrid mooring lines of Truss Spar in deep sea   by Yanzhe Wang Abstract: Truss Spar platform is one of most optimal solutions to the oil and gas exploration. In severe environments, the design of mooring lines is vital for the platform. As traditional steel chain is very heavy, synthetic rope is attractive for its lightness. Considering the dynamically coupled interaction between the hull of Truss Spar and mooring lines, the dynamic coupling analysis is performed to get the motion and line tension responses. The dynamic stiffness of synthetic rope is modelled as upper-lower critical stiffness model. The upper critical stiffness is used to calculate the motions, while the lower critical stiffness is for the line tension. Results show that the hybrid mooring lines could secure the platform sufficiently. Higher pre-tension could improve the stiffness of the system, make full use of the mooring lines and limit the motions. From the responses, we can conclude that the energy dissipation is located in the low frequency and middle frequency. The above observations made based on a Truss Spar may have important implications for other floating structures moored by a synthetic rope mooring lines. Keywords: synthetic rope; dynamic stiffness; pre-tension; coupled analysis; dynamic response; mooring line design; Truss Spar. Model-based development of MAV altitude control via ground-based equipment   by Stephen Wright Abstract: This paper presents the development and demonstration of an automated altitude controller for a very low weight Micro Air Vehicle (MAV) (i.e. less than 15 g), via low-cost ground-based equipment, and without the provision of active telemetry data from the airframe: this approach contrasts with current technologies that generally seek to place greater functionality within the airframe itself. It is shown that development of a suitable control algorithm is most efficiently achieved by simultaneous creation of an adequate airframe dynamic model, allowing stable control laws to be developed away from the unpredictable flight-test environment and adequate model development to be closely verified against flight-test data. The methodology is practically demonstrated with a simple commercial-off-the-shelf (COTS) MAV whose internal stabilisation controller is not available for modification and has no facility for transmission of airframe parameters to the controlling ground-station. Keywords: quadcopter; UAV; MAV; micro air vehicle; visual tracking; control; ground effect; modelling. Small signal stability analysis and optimised control of a PMSG-based wind turbine using differential evolution   by Shubhranshu Mohan Parida, Pravat Kumar Rout Abstract: Small signal stability of power system is has been analysed in the past few decades, but not much attention has been paid to the systems with wind turbines. This paper presents a detailed mathematical model to perform the small signal analysis of a direct-drive permanent magnet synchronous generator (PMSG). Based on the eigenvalue trajectories with varying controller parameters, the limits of proportional integral controller gains are decided within which the system remains stable. Further, the differential evolution algorithm is applied to an objective function based on eigenvalue shifting to find the optimal values of the controller gains within the decided limits. The time domain simulation results with the optimised controller gains are obtained using MATLAB software. The results demonstrate the stability of the system after initiating a small disturbance in terms of wind speed variation. Keywords: proportional integral; voltage source converters; permanent magnet synchronous generator; wind energy conversion system; differential evolution. Identification of multi-model LPV model with two scheduling variables using transition tests   by Jiangyin Huang Abstract: This paper presents the research findings of an identification method for LPV models with two scheduling variables using transition tests. The LPV model is parameterised as blended linear models, which is also called a multi-model structure. The identification method proposed can be used in batch process identification. The usefulness of the method is verified by modelling a high purity distillation column. The outputs of the LPV models are compared and analysed with three kinds of weighting functions, namely linear, polynomial and Gaussian functions. The case study shows that the multi-model LPV models can yield a better model accuracy with respect to simulation outputs and step response fittings than linear models. Keywords: LPV model; multi-model; transition test; high purity distillation column. Modelling of aerodynamic interference of 3-DOF GyroWheel rotor   by Xin Huo, Sizhao Feng, Xiaokun Liu, Qing Zhao, Hui Zhao Abstract: GyroWheel is an integrated mechanism that provides both attitude control torques and measurement of attitude angular rates for tiny spacecraft; however, aerodynamic interference is inevitable in the process of ground tests, which hinders the improvement of the system performance. In this paper, the modelling issue of aerodynamic interference with respect to the 3-DOF GyroWheel rotor is investigated. Based on the analysis of force distributions associated with each degree of freedom, the dynamical model of the GyroWheel rotor is established with Eulers method. According to the analysis of medium flow field, the mathematical model of the aerodynamic interference is formulated by using the boundary layer theory and N-S (Navier-Stokes) equations, illustrated by some numerical simulations in the environment of FLUENT. Keywords: GyroWheel rotor; aerodynamic interference; boundary layer theory; N-S equations. Adaptive Neural Networks for AC Voltage Sensorless Control of Three-Phase PWM Rectifiersby Adel RAHOUI, Hamid SEDIKI, Ali BECHOUCHE, Djaffar OULD ABDESLAM Abstract: In this paper, a new adaptive grid voltages estimator for AC voltage sensorless control of three-phase pulse-width modulation (PWM) rectifier is proposed. The proposed method is based on a simple adaptive neural network (ANN) to estimate online the grid voltages. The main advantage of this method is its simplicity and it requires low computational cost. The ANN estimator is inserted in voltage-oriented control (VOC) to perform an AC voltage sensorless control scheme. During the startup process, the proposed ANN estimator is also used for estimating initial values of the grid voltages. For accurate estimation, adaptive neural filters (ANFs)-based pre-filtering stage of the input voltages and AC-line currents is added. Experimental tests are carried out to verify the feasibility and robustness of the proposed ANN estimator. Experimental results show good performances of the proposed AC voltage sensorless control scheme in normal and severe grid voltage conditions. Keywords: Adaptive neural network (ANN), Adaptive neural filter (ANF), pulse-width modulation (PWM) rectifier, diode rectifier, grid voltages estimation, voltage-oriented control (VOC), sensorless control, startup process, experimental verification, stability Time Delay Finite Time Control of Unified Power Flow Controller for Power Flow Reference Trackingby Amar HAMACHE, Mohand Outahar BENSIDHOUM, Hachemi CHEKIREB Abstract: This paper presents a Time Delay Finite Time Controller (TDFTC) applied to a unified power flow controller (UPFC) to achieve rapid and finite time reference signal tracking of power flow in presence of plant uncertainties. The TDFTC is a nonlinear control based on the time delay disturbance estimator and the Lyapunov's stability theory to estimate the disturbances and cancel them. The TDFTC overcomes the drawback of traditional linear PI control, which is typically tuned for one specific operating condition and reduces chattering by using lower design gains. In this paper, first a state space complete dynamic model of UPFC is established based on Kirchhoff’s equations and (d-q) transformation and then TDFTC law is developed for the UPFC system. The proposed control is validated via a detailed simulation on a two bus system. Simulation results show power, effectiveness, robustness and accuracy of the proposed controller. Keywords: Power Flow; Unified Power Flow Controller; Time Delay Estimation; Finite Time Control; Lyapunov Function Robust path tracking control for quadrotors with experimental validation   by Wesam Jasim, Dongbing Gu Abstract: In this paper, we consider the autonomous path tracking control problem of quadrotors in the presence of external disturbances and model parameter uncertainties. A robust controller is derived and tested in simulation and practically on an AscTec Hummingbird quadrotor via $H_{\\infty}$ optimal design approach. The stability analysis was obtained via a selected Lyapunov function. Simulation results are compared with those of the integral backstepping controller. Practically, the $H_{\\infty}$ controller was used to perform several manoeuvres, such as take-off, square, circle, spiral and landing. Both simulation and practical results verified the stability and robustness of the proposed controller in the presence of external disturbances and model parameter uncertainties. Keywords: $H_{\\infty}$ controller; integral backstepping controller; path tracking; UAV quadrotor. Adaptive and modified adaptive control for pressure regulation in a hypersonic wind tunnel   by S.H. Rajani, Bindu M. Krishna, Usha Nair Abstract: Hypersonic wind tunnels are used for investigating the aerodynamic properties of vehicles during re-entry missions. This paper aims at designing a model reference adaptive control (MRAC) and modified adaptive control (MAC) for regulation of pressure inside the settling chamber of a hypersonic wind tunnel. MRAC is designed based on the MIT rule for a selected reference model. For improving the performance characteristics, MAC is designed by incorporating suitable modifications to the cost function and control law of MRAC. The dynamic characteristics of settling chamber pressure with model reference adaptive control as well as modified adaptive control are studied by numerical simulations of hypersonic wind tunnel model. Results show that the proposed modified adaptive control scheme is highly efficient in controlling the settling chamber pressure within a very short settling time and zero overshoot with an added advantage of overcoming the chatter effect. Keywords: adaptive controller; hypersonic wind tunnel; modified adaptive controller; nonlinear system; settling chamber pressure. Complete Synchronization of Supply Chain System Using Adaptive Integral Sliding Mode Control Methodby Hamed Tirandaz Abstract: In this paper, synchronization problem of supply chain chaotic system is carried out with active and adaptive integral sliding mode controlling method. Active integral sliding mode synchronization is performed for two identical supply chain systems by assuming that all parameters of the systems are known. When the internal and external distortion parameters of the system are considered unknown, an appropriate feedback controller is developed based on the adaptive integral sliding mode control mechanismrnto synchronize two identical supply chain chaotic systems and to estimate the unknown parameters of the systems. The stability evaluation of the synchronization methods are performed by the Lyapunov stability theorem. In addition, the performance evaluation of the designed controllers and the theoretical analysis are verified by some illustrative numerical simulations. Simulation results indicate excellent convergence from both speed and accuracy points of view. Keywords: Supply chain system, Integral sliding mode control, Active control, Adaptive control Enhanced receding horizon optimal performance for online tuning of PID controller parameters   by Shaoyuan Li, Yongling Wu, Kang Li Abstract: In this paper, a new online Proportional-Integral-Derivative (PID) controller parameter optimisation method is proposed by incorporating the philosophy of the model predictive control (MPC) algorithm. The future system predictive output and control sequence are first written as a function of the controller parameters. Then the PID controller design is realised through optimising the cost function under the constraints on the system input and output. The MPC-based PID online tuning easily handles the constraints and time delay. Simulation results in three situations, changing the control weight, adding constraints on the overshoot, and control signal and changing the reference value, confirm that the proposed method is capable of producing good tracking performance with low energy consumption and short settling time. Keywords: online parameter optimisation; PID controller; model predictive control; tracking performance; control energy. Estimation of the order and the memory of Volterra model from input/output observations   by Safa Chouchane, Kais Bouzrara, Hassani Messaoud Abstract: This paper proposes a new method to estimate, from input/output measurements, the structure parameters (order and memory) of Volterra models used for describing nonlinear systems. For each structure parameter (order and memory), the identification method is based on the definition, for increasing values of such parameters, of a specific matrix the components of which are lagged inputs and lagged outputs. This matrix becomes singular once the parameter value exceeds its exact value. The proposed method is tested in numerical examples, then it is used to model a chemical reactor. The results are successful. Keywords: nonlinear system; Volterra model; structure estimation; determinant ratio. Fault diagnosis and fault-tolerant control for the non-Gaussian nonlinear stochastic distribution control system using Takagi-Sugeno fuzzy model   by Lina Yao Abstract: For the non-Gaussian nonlinear stochastic distribution control system using Takagi-Sugeno fuzzy model, the nonlinear dynamic system is converted into a linear system. A fault diagnosis algorithm using RBF neural network and a sliding mode fault-tolerant control algorithm is presented. A new adaptive fault diagnosis algorithm is adopted to diagnose the gradual fault that occurs in the system, and the stability of the observation error system is proved. A differential evolution algorithm is used to optimise the central vector and width vector of RBF neural network. The sliding mode control algorithm is used to reconfigure the controller, based on the fault estimation information. The post-fault probability density function can still track the given distribution. Finally, simulation results show the effectiveness of the proposed fault diagnosis and fault-tolerant control algorithm. Keywords: fault diagnosis; RBF neural network; differential evolution; fault-tolerant control; sliding mode control. Prescribed performance control for MDF continuous hot pressing hydraulic system   by Liangkuan Zhu, Zibo Wang, Xiaodong Shao, Yaqiu Liu Abstract: In this paper, a prescribed performance control scheme is proposed for a medium density fibreboard (MDF) continuous hot pressing hydraulic system. The performance issues regarding transient and steady state behaviours are explicitly considered in the control design and analysis. First, a special error transformation is introduced into the first subsystem to transform original system with performance constraints into an equivalent 'output constrained' one to achieve prescribed performance guarantees. Subsequently, based on an appropriately designed barrier Lyapunov function (BLF), a controller is designed to stabilise the transformed system. Meanwhile, the novel error transformation effectively facilitates the control law derivation. It is proven that the proposed controller is capable of guaranteeing the satisfaction of the specific constraints on the transformed error and hence the prescribed performance specifications on the position tracking error, as well as the bounds of all closed-loop signals. In particular, in the second step of the controller design, a first-order filter is used in conjunction with the traditional backstepping control to eliminate the differential term expansion caused by the derivative of virtual control input. Finally, numerical simulation results are presented to authenticate and validate the effectiveness of the proposed control scheme. Keywords: medium density fibreboard; hydraulic system; guaranteed transient performance; barrier Lyapunov function; backstepping control; first-order filter. Self-adaptative multi-kernel algorithm for switched linear systems identification   by Lamaa Sellami Abstract: This paper deals with the identification problem of switched linear systems based on a measurement dataset. The great challenge of this problem lies in the dataset available for identification. Indeed, this set is a mixture of observations generated by a finite set of different linear submodels that interchange between each other with an unknown and unavailable switching dynamics. To overcome this problem, we developed an identification approach that consists of determining simultaneously a linear regression function that models each submodel and a switching signal estimation via a self-adaptive clustering algorithm. The regression function is identified based on the multi-kernel Support Regression Vector (SVR) approach. This identification approach consists of decomposing the regression vector into several blocks and assigning a kernel function to each block. However, the switching signal estimate is provided by an unsupervised classification algorithm with self-adaptive capacities. According to a similarity measure, this identification process is achieved through three main stages: classes creation (with an initialisation procedure), online classes adaptation and classes fusion. To evaluate the performance of the proposed method we include some simulation results. Keywords: switched linear systems; system identification; multi-kernel support regression; machine learning. Intensity-curvature highlight of human brain magnetic resonance imaging vasculature   by Carlo Ciulla, Ustijana Rechkoska Shikoska, Dimitar Veljanovski, Filip A. Risteski Abstract: This paper uses the concept of intensity-curvature to highlight human brain vasculature imaged through Magnetic Resonance Imaging (MRI). Two model functions are fitted to the MRI data. The model functions are: (i) the bivariate cubic polynomial (B32D), and (ii) the bivariate cubic Lagrange polynomial (G42D). The sum of all of the second order partial derivatives with respect to the independent variables of the model function is calculated and is called classic-curvature. The classic-curvature is therefore a function of the independent variables and it can be calculated at the origin (0, 0) of the pixel coordinate system and also at any intra-pixel coordinate (x, y). The antiderivative of the product between the classic-curvature calculated at (0, 0) and the image pixel intensity is called intensity-curvature term (ICT) before interpolation. The antiderivative of the product between the classic-curvature calculated at (x, y) and the model function is called intensity-curvature term (ICT) after interpolation. When the two intensity-curvature terms are calculated on a pixel-by-pixel basis across the image, they become two additional images. Through the use of the aforementioned ICT images, it is possible to highlight and filter the human brain vasculature imaged with MRI. Moreover, the inverse Fourier transformation of the difference between the k-space of the MRI and the k-space of the ICT provides vessel identification. In essence, this research presents evidence that MRI images of the human brain can be studied through two additional domains: the intensity-curvature terms. Keywords: bivariate cubic polynomial model; bivariate cubic Lagrange polynomial model; intensity-curvature term before interpolation; intensity-curvature term after interpolation; magnetic resonance imaging; k-space; human brain; vasculature. Stabilisation of a class of non-minimum phase switched nonlinear systems based on backstepping method   by Arwa Abdelkrim, Khalil Jouili, Naceur Benhadj Braiek Abstract: This paper addresses the formalism of the input-output feedback linearisation applied to a certain class of switched nonlinear systems, where each mode may be a non-minimum phase, to design state feedback controllers and a switching law based on multi-Lyapunov functions. The performed developments are largely based on a backstepping approach and multiple Lyapunov functions. The state feedback controllers and the switching law are developed to stabilise the transitions between the stability regions associated with each mode with non-minimum phase. Finally, simulation results of a non-minimum phase continuously stirred tank reactor show the effectiveness of the method. Keywords: backstepping; stabilisation; switched nonlinear systems; non-minimum phase; multiple Lyapunov functions; input–output feedback linearisation. Adaptive Decentralized Sliding Mode Controller and Observer for Asynchronous Nonlinear Large Scale Systems with Backlashby Ahmad Taher Azar, Fernando E. Serrano Abstract: In this article an adaptive decentralized sliding mode controller and observer for asynchronous nonlinear large scale systems with backlash is proposed. Considering that in the literature, only the synchronous case for input non-linearities such as dead-zone and saturation are found. In this article, the asynchronous case for systems with backlash is studied considering the backlash effect. Due to the complexity of the backlash non-linearity, an adaptive decentralized controller is proposed because of the capability of this strategy to deal with uncertainties and to improve the system performance when this non-linearity is found. Additionally a decentralized sliding mode observer is proposed in order to estimate the states of the system. Keywords: Decentralized Control; Switched Systems; Sliding Mode Control;\r\n Asynchronous Control D-stability of parameter-dependent linear systems including discretization by Taylor series expansion and search in a scalar parameter.by Marco Aurelio Leandro, karl Kienitz Abstract: This work addresses the allocation of the closed-loop poles of a discretized system from a continuous-time one with varying parameters, aiming at its control through a computer. It proposes a sufficient condition for an allocating state feedback with parameter-dependent gain. The condition is veri ed through a feasibility test of a set of Linear Matrix Inequalities (LMIs), based on the existence of a homogeneous polynomially parameter-dependent Lyapunov function of arbitrary degree. The main contribution of this work is the guarantee of the continuous-time system's stability and simultaneously the allocation of the closed-loop poles of the discretized system in a D-stable region. In order to allow this, the discretized model is formed by homogeneous polynomial matrices of arbitrary degree, augmented by an additive norm-bounded term, which represents the discretization residual error. Numerical examples show a larger number of feasible cases associated to the proposed condition in comparison with the condition based on a parameter-independent gain. Keywords: Robust control; D-stability; discrete-time linear systems; parameter-dependent state feedback; linear matrix inequalities. A novel four-dimensional conservative chaotic system without linear term, its analysis and adaptive control via integral sliding mode controlby Sundarapandian Vaidyanathan Abstract: In this work, a novel conservative four-dimensional chaotic system without linear term has been proposed. The fundamental qualitative properties of the novel chaotic system are described with details of volume preserving property, equilibrium points, symmetry, Lyapunov exponents and Kaplan-Yorke dimension. We show that the novel four-dimensional chaotic system has two planes and one line of equilibrium points. Next, an adaptive integral sliding mode controller is designed to stabilize the novel chaotic system with an unknown system parameter. Moreover, an adaptive integral sliding mode controller is designed to achieve global chaos synchronization of the identical novel chaotic systems with an unknown system parameter. The adaptive control mechanism helps the control design by estimating the unknown parameter. Numerical simulations using MATLAB are shown to illustrate all the main results derived in this work. Keywords: Chaos; chaotic systems; novel system; adaptive control; sliding mode control; chaos synchronization. Feedback control of bilinear distributed parameter system by input-output linearizationby Nouara HABRACHE, Ahmed MAIDI, Jean-Pierre Corriou Abstract: In this paper, a control law that enforces the tracking of a boundary controlled output for a bilinear distributed parameter system is developed in the framework of geometric control. The dynamic behavior of the system is described by two weakly coupled linear hyperbolic partial differential equations. The stability of the resulting closed-loop system is investigated based on eigenvalues of the spatial operator of a weakly coupled system of balance equations. It is shown that, under some reasonable assumptions, the stability condition is related to the choice of the tuning parameter of the control law. The performance of the developed control law is demonstrated, through numerical simulation, in the case of a co-current heat exchanger. The control objective is to control the outlet cold fluid temperature by manipulating its velocity. Both tracking and disturbance rejection problems are considered. Keywords: partial differential equation; bilinear distributed parameter system; geometric control; characteristic index; exponential stability; co-current heat exchanger Whole Body Motion Generation of 18-DOF Biped Robot on Flat Surface during SSP & DSPby Ravi Kumar Mandava, Pandu Ranga Vundavilli Abstract: The present work explains the dynamically balanced gait generation of 18-DOF biped robot on a flat surface during both double support phase (DSP) and single support phase (SSP).To generate the said gaits, cubic polynomial trajectories are assumed to be followed by the swing foot and wrist end of the hand. Further, the hip joint is assumed to follow a straight line and cubic polynomial trajectories in the sagittal and frontal planes, respectively. A closed form solution methodology based on inverse kinematics is used for determining the joint angles made by various links of the biped robot. Once the gait related to upper and lower limbs of the two legged robot is generated, the balance of the generated gait is decided by finding the position of zero moment point (ZMP). Moreover, Lagrange–Euler formulation is used for calculating the dynamics of the biped robot. Further, the effectiveness of the developed algorithm in terms of generating dynamically balanced gaits on flat surface has been verified in computer simulations. Further, the generated gait has been tested on a real biped robot. Keywords: Biped robot, single support phase, double support phase, dynamic balance margin A Chattering-free Adaptive Second-order Nonsingular Fast Terminal Sliding Mode Control Scheme for A Class of Nonlinear Uncertain Systemsby Beibei Zhang, Dongya Zhao Abstract: In this paper, an adaptive second-order nonsingular fast terminal sliding mode (SONFTSM) control scheme is proposed so as to achieve finite-time stability with chattering-free control inputs for a class of nonlinear uncertain systems. Instead of the traditional control input in primitive sliding mode switching control design, the real control input is the time integration of the designed derivation of control input with discontinuous terms such that the chattering phenomenon can be reduced. An integral terminal sliding mode (ITSM) and a nonsingular fast terminal sliding mode (NFTSM) are applied into the equivalent control design such that finite-time convergence of system states can be guaranteed when it motions on sliding surface. Then, an adaptive method are utilized to estimate the unknown upper bound of the lumped uncertainty caused by modelling error and external disturbance. The stability analysis of close-loop system can be demonstrated by constructing Lyapunov candidate function. Finally, the simulation results verify the effectiveness of proposed control scheme. Keywords: Nonsingular fast terminal sliding mode; Integral terminal sliding mode; Adaptive method; Lyapunov candidate function; Nonlinear uncertain systems. Fault Diagnosis and Model Predictive Fault Tolerant Control For Stochastic Distribution Collaborative Systemsby Yunfeng Kang, Ling Zhao, Lina Yao Abstract: This paper presents a fault-tolerant control scheme for a class of stochastic distribution collaborative control systems, which are composed of two subsystems connected in series to complete the target. The output of the whole system is the output probability density function (PDF) of the second subsystem. To diagnose the fault in the first subsystem, an adaptive diagnostic observer and linear matrix inequality (LMI) technique are used to obtain the adaptive tuning law to estimate the fault. When fault occurs, the fault itself can not be compensated in the first subsystem and a model predictive controller is designed in the second subsystem to compensate the fault, making the post-rnfault output PDF still track the desired PDF as close as possible. A simulated example is given and desired results have been obtained. Keywords: Stochastic distribution collaborative control systems; Fault diagnosis (FD); Fault tolerant control (FTC); Model predictive control (MPC); Linear matrix inequality (LMI) Bolt Quality Testing Research Using Weighted Fusion Algorithm Based on Correlation Functionby Xiaoyun Sun, Hui Xing, Guang Han, Jiulong Cheng, Yongbang Yuan, Jianpeng Bian, Haiqing Zheng, Mingming Wang Abstract: Bolt length is an important factor for quality evaluation of anchor. Because of the harsh detection environment and the interference caused by instruments, bolt testing signal contains a lot of noise which makes it difficult to analyse and predict the parameters of anchor bolts accurately. In this paper, a non-destructive method based on information fusion of pseudo random signals is presented for bolt quality testing. After pseudo-random signals are generated by multiple sources, weighted fusion algorithm based on correlation function is proposed for fusion processing. Compared with the D-S fusion algorithm and average weighted approach, the correlation fusion is verified to have higher accuracy and better retention of frequency characteristic. Finally, this proposed approach is proved to be more suitable for random signal fusion. Keywords: anchor bolt; nondestructive testing; D-S fusion algorithm; Weighted fusion based on correlation function Variational principle for stochastic singular control of mean-field Lévy-forward-backward system driven by orthogonal Teugels martingales with application   by Mokhtar Hafayed, Shahlar Meherrem, Deniz H. Gucoglu, Saban Eren Abstract: We consider stochastic singular control for mean-field forward-backward stochastic differential equations, driven by orthogonal Teugels martingales associated with some Lévy processes having moments of all orders and an independent Brownian motion. Under partial information, necessary and sufficient conditions for optimality in the form of maximum principle for this mean-field system are established by means of convex variation methods and duality techniques. As an illustration, this paper studies a partial information mean-variance portfolio selection problem driven by orthogonal Teugels martingales associated with gamma process as Lévy process of bounded variation. Keywords: controlled forward-backward system; maximum principle; orthogonal Teugels martingales; Lévy processes; singular control; mean-field stochastic system; partial information; gamma process.DOI: 10.1504/IJMIC.2017.10006366  An adaptive and selective segmentation model based on local and global image information   by Xueqin Wang, Shurong Li, Jiaojiao Li, Jiayan Wang Abstract: This study investigates the application of partial differential equations in image segmentation field. A novel selective segmentation mode is proposed for the existing selective segmentation model which cannot segment the intensity inhomogeneity and fuzzy edge image. In this novel model, a weighting function based on local information is constructed. This weighting function can introduce the global and local information of the image into the novel model which can realise the adaptive segmentation of the image. Compared with the existing selective segmentation model, the novel selective segmentation model proposed in this paper can realise the adaptive segmentation of intensity inhomogeneity and fuzzy edge images. Experimental results show that the novel model is more effective and adaptive to segment images with intensity inhomogeneity or fuzzy edge, and less sensitive to the location of initial contour, without choosing the weighting parameter between global and local information by manual method. Keywords: selective segmentation; intensity inhomogeneity image; adaptive segmentation; level set method; weighting function; global and local information.DOI: 10.1504/IJMIC.2017.10006365  Controlling a mobile manipulator actuated by DC motors and a single phase H-bridge inverter   by Amal Karray, Moez Feki Abstract: In this paper, we treat the dynamic feedback control of a mobile manipulator actuated by DC motors using a digital pulse width modulation (DPWM) and a single phase H-bridge inverter in order to achieve a desired trajectory. Firstly, a fuzzy proportional-derivative (PD) controller is proposed to provide the necessary torques for the motion of the robot and to eliminate the effect of external force on the end-effector. Secondly, we aim to determine the current signal needed to drive the DC motors using an H-bridge inverter. Simulation results are given to show the effectiveness of the proposed controller and to demonstrate the coordination of two subsystems in performing the desired trajectory. Keywords: non-holonomic mobile robots; DC motors; H-bridge inverter; fuzzy control; desired trajectory tracking.DOI: 10.1504/IJMIC.2017.10006367  Mechanical analysis of a dual derrick   by Xingping Xu, Guangdou Liu, Hai Wang, Yanzhe Wang, Zhihui Liu, Xin Zhang, Longting Wang Abstract: Dual derrick can greatly improve the efficiency of drilling operations in deep-water area. Analysis of various drilling processes such as single-well drilling, multi-well drilling, collaboration and parallel jobs using dual derrick frame, has been carried out in this research. Meanwhile, static analysis of dual derrick and the analysing of loading cases have been conducted, as well as the suffered stress of dual derrick under severe or normal drilling conditions. Modal analysis of dual derrick has been completed, also, dynamic equilibrium equations and the matrices of corresponding mass and stiffness have already been induced. Concerning the fact that higher modes have a slight impact on vibrations, eight low-level modes of vibration of dual derrick have been put forward, which turn out to match the optimised structure of vibration modes. Keywords: dual derrick; mechanical model; static analysis; modal analysis.DOI: 10.1504/IJMIC.2017.10006364  Modelling and simulation: an improved RANSAC algorithm based on the relative angle information of samples   by Chengbo Liu, Qiang Shen, Hai Pan, Miao Li Abstract: Random sample consensus (RANSAC) algorithm is the most widely used one in the field of computer vision. In order to reduce the high complexity of RANSAC, this paper proposes a novel method which can reject samples before calculating the homography matrix. This algorithm can eliminate random samples that may be wrong through calculating the relative angle information of the random samples, and then, use the correct samples for the next step. The algorithm can ensure the accuracy of the premise while greatly reducing the computational complexity. Not only that, the improved algorithm can also be combined with the existing RANSAC extensions to improve the computational efficiency. Keywords: reject samples; homography matrix; random sample consensus; RANSAC; relative angle; verify model.DOI: 10.1504/IJMIC.2017.10006363  Analysis, synchronisation and circuit implementation of a novel jerk chaotic system and its application for voice encryption   by Sundarapandian Vaidyanathan, Aceng Sambas, Mustafa Mamat, Mada Sanjaya WS Abstract: In this research work, a novel 3D jerk chaotic system with one-quadratic nonlinearity and two-cubic nonlinearities is designed to generate complex chaotic signals. We show that the novel jerk chaotic system has a unique equilibrium at the origin, which is a saddle-focus and unstable. The Lyapunov exponents of the novel jerk chaotic system are obtained as L1 = 0.30899, L2 = 0 and L3 = -4.11304. The Kaplan-Yorke dimension of the novel jerk chaotic system is obtained as DKY = 2.0751. The qualitative properties of the novel jerk chaotic system are described in detail and MATLAB plots are shown. Next, we use backstepping control method to establish global chaos synchronisation of the identical novel jerk chaotic systems with unknown parameters. Next, an electronic circuit realisation of the novel jerk chaotic system is presented using MultiSIM to confirm the feasibility of the theoretical model. Finally, we present an application of the novel jerk chaotic system for voice encryption. The comparison between the MATLAB 2010 and MultiSIM 10.0 simulation results demonstrate the effectiveness of the proposed voice encryption scheme. Keywords: chaos; chaotic systems; jerk systems; Lyapunov exponents; chaos synchronisation; backstepping control; circuit implementation; voice encryption.DOI: 10.1504/IJMIC.2017.10006361  Low voltage ride-through capability improvement of doubly fed induction generator using series connected damping resistances   by Youness Boukhris, Aboubakr El Makrini, Hassan El Moussaoui, Hassane El Markhi Abstract: This paper proposes a control strategy to improve low voltage ride through (LVRT) capability of doubly fed induction generator (DFIG)-based wind turbines in response to grid fault occurrences or grid fault clearances to follow the requirements defined by the grid codes. The proposed scheme involves the use of series connected damping resistances (SCDR) and bypass switching devices coupled with rotor side converter (RSC), by which current peaks at both the rotor side and stator side can be reduced. The steady state behaviour under normal condition and dynamic behaviour of DFIG-based wind turbines during grid faults using the proposed strategy is simulated and assessed, and the results are compared with the scheme using crowbar circuit. Keywords: wind turbine; doubly fed induction generator; DFIG; grid fault; low voltage ride through; LVRT; damping resistances; rotor side converter; RSC; grid side converter; GSC.DOI: 10.1504/IJMIC.2017.10006368  A new implementation of an impulsive synchronisation of two discrete-time hyperchaotic systems using Arduino-Uno boards   by Hamid Hamiche, Ouerdia Megherbi, Redouane Kara, Saïd Djennoune, Rafik Saddaoui, Mourad Laghrouche Abstract: In this paper, we present experimental results on impulsive synchronisation between two discrete-time hyperchaotic systems. In the first part, we give some sufficient conditions on the asymptotic synchronisation by using varying impulsive distance in order to guarantee the impulsive synchronisation of the two mentioned systems. Numerical simulations are provided to show the effectiveness of the method. Next, an easy experimental implementation is realised using the Arduino-Uno boards. The obtained experiment results validate the proposed approach. Keywords: hyperchaotic system; impulsive observer; impulsive synchronisation; experimental realisation; Arduino-Uno boards.DOI: 10.1504/IJMIC.2017.10006362  Solutions to fuzzy variational problems: necessary and sufficient conditions   by Mohammad Heidari, Mohadeseh Ramezanzadeh, Akbar Hashemi Borzabadi, Omid Solaymani Fard Abstract: The aim of this study is to investigate the necessary and sufficient conditions for fuzzy variational problems. To this purpose, based on a parametric representation for the α-level set of a fuzzy valued function, the fuzzy variational problems are converted to general variational problems in a parametric form. The Euler-Lagrange equations as necessary optimality conditions are derived, and then the solutions of these equations lead to the construction of the α-level sets of fuzzy extremal solutions for the original problems. Moreover, a sufficient condition under an appropriate convexity assumption is discussed for fuzzy variational problems. Using an example, the effectiveness of the proposed technique is discussed by comparing with the results of the given approaches in Fard et al. (2014) and Farhadinia (2011). Keywords: fuzzy valued functions; fuzzy variational problems; fuzzy isoperimetric problems; necessary and sufficient conditions.DOI: 10.1504/IJMIC.2017.10006369  Control design approaches for parallel robot manipulators: a review   by Ahmad Taher Azar, Quanmin Zhu, Alaa Khamis, Dongya Zhao Abstract: In this article, different control design approaches for parallel robot manipulators are presented with two distinguished classes of control strategies in the literature. These are the model-free control and the dynamic control strategy, which is mainly a model-based scheme, and is mostly the alternative when the control requirements are more stringent. The authors strongly believe that this paper will be helpful for researchers and engineers in the field of robotic systems. Keywords: parallel manipulator; serial manipulator; model-free control techniques; model-based control techniques; real-time dynamic substructuring; RTDS.DOI: 10.1504/IJMIC.2017.10007051  Cascade ADRC-based fault-tolerant control for a PVTOL aircraft with potential actuator failures   by Xinli Xu, Zhen Jiang, Huosheng Hu Abstract: This paper presents a novel reconfigurable control method for the planar vertical take-off and landing (PVTOL) aircraft with potential actuator failures. A cascade active disturbance rejection controller (ADRC) is used to counteract the adverse effects when the actuator failure occurs. The coordinate transformation is used for model decoupling due to the severe coupling between some variables. This approach does not require the accurate mathematical model of the controlled system and ensures that the reference input value can be tracked rapidly and accurately. The stability and safety of the aircraft is much improved in the event of actuator failures. Finally, the simulation results are given to show the effectiveness and performance of the developed method. Keywords: cascade ADRC; planar vertical take-off and landing; PVTOL aircraft; coordinate transformation; fault-tolerant control; FTC; actuator failure.DOI: 10.1504/IJMIC.2017.10007050  Identification of a stochastic resonate-and-fire neuronal model via nonlinear least squares and maximum likelihood estimation   by Jun Chen, Peter Molnar, Aman Behal Abstract: Recent work has shown that the resonate-and-fire neuronal model is both computationally efficient and suitable for large network simulations. In this paper, we examine the estimation problem of a resonate-and-fire neuronal model with stochastic firing threshold. The model parameters are divided into two sets. The first set is associated with the subthreshold behaviour and can be estimated by a least squares algorithm, while the second set includes parameters associated with the firing threshold and its identification is formulated as a maximum likelihood estimation problem. The latter is in turn solved by a simulated annealing approach that avoids local optima. The proposed identification approach is evaluated using both simulated and in-vitro data, which shows a good match between prediction by identified model and the actual data, concluding the efficiency and accuracy of the proposed approach. Keywords: resonate-and-fire; neuronal model; stochastic threshold; parameter estimation; maximum likelihood; simulated annealing.DOI: 10.1504/IJMIC.2017.10007053  MRAC base robust RST control scheme for the application of UAV   by Zain Anwar Ali, Dao Bo Wang, Muhammad Aamir, Suhaib Masroor Abstract: A hybrid control scheme is proposed in this paper to achieve the desired (position and altitude) tracking response of an unmanned aerial vehicle (UAV). The tri-rotor-based aircraft is selected to perform the simulations considering that the dynamic model of the UAV is already unstable, under-actuated and nonlinear in behaviour. The designed control scheme is used to produce the rotational velocities of UAV which are consequently handled by the hybrid controller. The hybrid controller consists of model reference adaptive control (MRAC) with regulation, pole-placement and tracking (RST) controller and the entire system stability is dealt with by MIT rules. The presented control scheme is tested via computer-based simulations to follow the desired position and attitude of UAV. The efficiency of the proposed scheme is compared with MRAC-based MIT rule and its validity is further checked with MRAC-based Lyapunov rule. The results show that the presented hybrid controller exhibits robustness, fast error convergence and a zero steady state error in the existence of model uncertainties and disturbances. Keywords: model reference adaptive control; MRAC; hybrid controller; MIT rule; unmanned aerial vehicle; UAV.DOI: 10.1504/IJMIC.2017.10007057  System identification of the quadrotor with inner loop stabilisation system   by Minhuan Guo, Yan Su, Dongbing Gu Abstract: In order to build the dynamic model of quadrotors with inner loop stabilisation system, a real-time system identification technique is developed in frequency domain with real flight data. Firstly, a second order transfer function is adopted as the low order equal system (LOES) for each channel. Then, a recursive discrete Fourier transformation (DFT) is detailed, which helps to calculate the recursive frequency spectrum of the inputs and outputs. Based on the latest frequency spectrum, the unknown parameters in LOES are calculated by a least squares method and then the observable canonical form of state space equations is given. Finally, the performance of the identified model is analysed in time-domain by calculating Theil's inequality coefficient and in frequency-domain by plotting Bode diagrams. The identified model is utilised for the design of tracking controllers. The experimental result validates the proposed method. Keywords: discrete Fourier transformation; DFT; least squares estimation; system identification; quadrotor; path tracking; PID.DOI: 10.1504/IJMIC.2017.10007049  Stable state dependent Riccati equation neural observer for a class of nonlinear systems   by Amin Sharafian, Reza Ghasemi Abstract: This paper proposes a new methodology for state estimation of a class of nonlinear systems. Owing to hard nonlinearity of some complex systems, the performance of linearisation methods is limited, thus this paper focuses on a new technique for nonlinear state estimation based on the combination of the state dependent Riccati equation (SDRE) and the neural network. SDRE technique is adapted to bring the certain nonlinear parts of system into linear-like structure and the unknown nonlinearities are estimated by artificial neural network whose weights are adjusted with guaranteed stability of the closed-loop system. This technique is strongly distinguishing the effect of uncertain nonlinearities and unmodelled dynamics to prevent divergence of state estimation error. Both the stability of the closed-loop system and uniform ultimate boundedness of the observer error are guaranteed based on Lyapunov theory. Keywords: state dependent Riccati equation; SDRE; state estimation; neural observer; nonlinear systems; Riccati equation.DOI: 10.1504/IJMIC.2017.10007056  Non-diagonal multivariable fractional prefilter in motion control   by Najah Yousfi-Allagui, Nabil Derbel, Pierre Melchior Abstract: A novel approach for robust Commande Robuste d'Ordre Non Entier (CRONE) control of multi input multi output (MIMO) systems using quantitative feedback theory (QFT) design is discussed through fractional prefilters with off-diagonal elements. More design flexibility is guaranteed when using the non-diagonal prefilter. For a given system, the CRONE control approach is combined with QFT design to get the controller matrix. After that, the classic diagonal fractional prefilter expression is extended to a fully populated prefilter matrix. The Davidson-Cole fractional prefilter optimisation is used to determine the diagonal terms of prefilter. The role of the off-diagonal elements of prefilter is to eliminate loop interactions in the case of reference tracking. So a sequential design procedure is proposed in order to get the fully populated prefilter matrix elements. The performance of the novel methodology is finally verified by adopting the designed prefilter and controller to govern the MIMO SCARA robot model. Keywords: CRONE control; coupling matrix; fractional prefilter; Davidson-Cole prefilter; multivariable control; MIMO systems; robust control; path tracking; quantitative feedback theory; QFT.DOI: 10.1504/IJMIC.2017.10007055  Optimal iterative learning control for a class of non-minimum phase systems   by Leila Noueili, Wassila Chagra, Moufida Lahmari Ksouri Abstract: In this paper, an optimal iterative learning control (ILC) approach is proposed for a class of repetitive non-minimum phase (NMP) systems. The control law synthesis is based on the resolution of a quadratic criterion which minimises the errors between the setpoint references and the system outputs at each iteration for each trial. The resolution of the control problem uses a new gain which avoids matricial inversion problems appearing in classical ILC algorithms such as direct model inversion (I-ILC) and optimal ILC (Q-ILC). The new optimal ILC approach improves the learning convergence significantly compared to the previously mentioned algorithms. Furthermore, sufficient and necessary stability conditions are established with convergence properties. The effectiveness of the proposed method is proved by simulations with an NMP mass-spring damper system. Keywords: learning control; inverse model ILC; optimal ILC; alpha-ILC; MIMO systems; non-minimum phase systems.DOI: 10.1504/IJMIC.2017.10007052  Special Issue on: ICMIC 2015 Sliding Mode Control, Theory and Application Discrete time quasi-sliding mode control of nonlinear uncertain systemsby Ibtissem Bsili, Jalel Ghabi, Hassani Messaoud Abstract: The control of nonlinear uncertain systems is still an open area of research, sliding mode control (SMC) is one of the robust and effective methods to cope with uncertain conditions. In this paper, a new sliding mode control algorithm for a class of discrete-time nonlinear uncertain systems is proposed. By using an estimator of uncertainties and external disturbances, the proposed algorithm ensures the stability of the closed loop system as well as the reference tracking. The controller designed using the above technique is completely insensitive to the parametric uncertainty and the external disturbances. Simulations are carried out on a numerical example and a bioreactor benchmark and the yielded results confirm the effectiveness of our proposition. Keywords: Discrete time quasi-sliding mode control, nonlinear systems, uncertain systems, estimator, a bioreactor benchmark Finite Frequency Observer Design for T-S Fuzzy Systems with Unknown Inputs: An LMI Approachby Chibani Ali, Chadli Mohammed, Benhadj Braiek Naceur Abstract: This papers investigates the problem of $H_{\infty}$ filtering for T-S fuzzy systems with unknown inputs.The frequency ranges of these external signals are assumed to be known beforehand and to belong in the low frequency band. The observer is designed in the low frequency domain such that the effects of the unknown inputs are attenuated to a specified level $\gamma$ by means of an $H_{\infty}$ performance norm. By exploiting the Generalized Kalman-Yakubovich-Popov (GKYP) lemma and the Lyapunov method, sufficient design conditions are derived in Linear Matrix Inequality (LMI) formulations for both continuous-time and discrete-time T-S fuzzy models. Finally an illustrative example is introduced to provide the effectiveness of the proposed approach. Keywords: Fuzzy Models; Unknown Inputs Observer; Finite Frequency Domain; LMI. A Novel Sliding Mode Controller Scheme for a Class of Nonlinear Uncertain Systemsby Jalel Ghabi Abstract: This paper considers a continuous sliding mode control for a class of nonlinear systems with uncertainties including both parameter variations and external disturbances. Under the framework of sliding mode and using the upper bounds of the uncertainties, the proposed controller is derived to guarantees the stability of overall closed-loop system and ensures robustness against modelling errors, parameter uncertainties and external disturbances. As for chattering elimination in sliding mode control, a boundary layer around the sliding surface is used and the continuous control is applied within the boundary. Moreover, an extended schema of a higher-order sliding mode controller is developed in this paper as another solution to avoid the problem of chattering effect. Simulation results demonstrate the efficacy of the proposed control methodology to stabilize an inverted pendulum, which is a standard nonlinear benchmark system. Although, the applicability of the proposed algorithm aims to be extended, via suitable modifications, to the case of multivariable nonlinear systems with uncertainties of more general type, covering a wide class of processes. Keywords: Nonlinear Systems, Uncertainty, Sliding Mode Control, Stability, Robustness, Inverted Pendulum, Higher-order sliding mode. Terminal Sliding Mode Control Based MPPT for a Photovoltaic System with Uncertaintiesby Wajdi Saad, Anis Sellami Abstract: Over the past few decades, the world demand for energy has risen steadily, forcing the world communities to look for alternative sources. Photovoltaic (PV) is seen as the most appropriate solution for this demand. In this context, this paper presents a robust terminal sliding mode control (RTSMC) method for maximum power tracking of stand-alone PV system. The design method provides good robustness proprieties face to the system uncertainties and change of environment conditions. Starting from the mathematical dependence between the open-circuit voltage (Voc) and the optimal operating voltage (Vop), an MPPT design method is given. To eliminate the tracking voltage error, a RTSMC method is introduced thereafter. A pulse width modulator (PWM) is used to maintain the switching frequency constant. Compared to the P&O algorithm, the proposed methodology reduces the oscillations around the maximum power point (MPP) and provides better performance proprieties. Also, the simulations results prove the robustness qualities of the TSMC-MPPT design method. Keywords: terminal sliding mode control; robust control; MPPT; photovoltaic system. Faults reconstruction for output time-delay systems: Sliding Mode Observer Approachby houaida cherni, Iskander Boulaabi, Anis Sellami, Fayçel Ben Hmida Abstract: This paper addresses actuator and sensor faults reconstruction based on a new Sliding Mode Observer (SMO) for output time-delay systems. Therefore, using the Lyapunov-Krasovskii functional, the stability of the estimation error dynamics is guaranteed. Also, the Linear Matrix Inequality LMIs technique is applied to express the observer synthesis. After that, the proposed SMO is used to obtain actuator and sensor faults reconstruction. To show the validity and the applicability of the proposed approaches, a numerical example is provided. Keywords: Sliding mode observer; actuator fault reconstruction; sensor fault reconstruction; time-delay systems; LMI technique. Distributed second order sliding mode control for networked robots synchronisation: theory and experimental resultsby Yassine Bouteraa, Nabil Derbel Abstract: The paper focuses on synchronization and trajectory tracking problems. The main goal of the distributed strategy is to produce and maintain a common behavior using only local information interactions. A combination of a trajectory tracking theory and a cross-coupling algorithms have been used to solve synchronization problems for a group of Lagrangian systems. A robust control law based on a modified high order sliding mode concept is developed. In the control architecture, the increment of the control responsible to the robustness of the proposed approach is not proportional to the sign of the sliding surface, but it is proportional to the integral of a sign function. The Lyapunov-based approach has been used to establish the multi-robot systems asymptotic stability. Experimental results are provided to demonstrate the performance of the proposed control schemes. Keywords: Second order sliding mode control; synchronization problems; trajectrory tracking. Special Issue on: ICEE2015 Signals and System Modelling, Design and Simulation On lambda-matrices and their applications in MIMO control systems design   by Belkacem Bekhiti, Abdelhakim Dahimene, Bachir Nail, Kamel Hariche Abstract: In the present paper we have introduced new control design algorithms based on the theory of matrix polynomials. The first procedure is called block decoupling control, which is based on the spectral factors of the denominator of the right matrix fraction description. The advantages of this control are the non-interacted behaviour, simplicity in control design and low order controller is obtained due to the cancellation property of the proposed algorithm. The second control algorithm is the whole set of latent-structure assignments via the approaches of block root placement. The procedure is developed even if the system is not block transformable. A process is done with the aid of conversion between state space and matrix fraction description. The last method is defined as a MIMO PID controller design via the placement of block roots with the help of Diophantine equation resolution, the latter systematic procedure retains both regulation and tracking objectives with small gains and minimum error. Keywords: block roots; spectral factors; right matrix fraction description; MIMO PID; Diophantine equation. PCB-planar transformers equivalent circuit model identification using genetic algorithm   by Aymen Ammouri, Tarek Ben Salah, Ferid Kourda Abstract: Planar passive components are interesting solutions for the design of integrated power converters. Models of planar magnetic devices are still not available in simulator tools. Therefore, there is a limitation during the design process of integrated power systems. In this paper, an equivalent circuit model for planar transformers is developed. The modelling of a planar transformers parasitic, such as its winding loss, magnetising inductance, leakage inductance or parasitic capacitance, have individually been investigated. The magnetising inductance remains a complex parameter to model, particularly when the problem of corner sections effects is taken into account. Skin and proximity effects in primary and secondary windings are modelled by a ladder R-L network. The ladder parameters are identified by a minimising function between experimental and simulation results using the genetic algorithm. During the validation process, three typical winding arrangements of the planar transformer have been investigated. The planar transformer model has been favorably evaluated by comparison and validation with experimental data and 3D finite element method. It is found that simulation results and data measurements are in close agreement with a planar transformer model. Keywords: PCB planar transformer; interleaving; leakage inductance; parasitic capacitance; winding loss; finite element methods; genetic algorithm. An interactive design strategy for fractional order PI controllers in LabVIEW   by Ali Yüce, Furkan Nur Deniz, Nusret Tan, Derek P. Atherton Abstract: This paper presents an interactive design for a fractional order PI (FOPI) controller based on Inverse Fourier Transform Method (IFTM) in accordance with the stability region of a closed loop control system in LabVIEW, which is a powerful graphical program. A Stability Boundary Locus (SBL) method is used to obtain the stability region, including all stabilising FOPI controller parameters in the (Kp, Ki) plane. The time response of the closed loop control system with FOPI controller is then obtained by IFTM, using the stabilising controller parameters selected from the stability region. Changing the selected fractional order controller parameters in the stability region, users can observe the step response of the system interactively. Keywords: fractional order PI controller; inverse Fourier transform method; stability boundary locus method; interactive design. Special Issue on: ICEE2015 Signals and System Modelling, Design and Simulation Design and real time implementation of hybrid fractional order controller for grid connected wind energy conversion systemby Antar Beddar, Hacen Bouzekri Abstract: This paper focuses on designing and real time implementation of Hybrid Fractional Order Controller (HFC) for grid connected variable speed Wind Energy Conversion System (WECS). The HFC was integrated to current vector control and Direct Current Control (DCC) to guarantee maximum power extraction and ensuring unity power factor of the grid side. The proposed HFC employs a conventional PI controller, a Fractional Order PI controller (FO-PI), and a Switching Algorithm (SA). The parameters of the HFC were calculated using frequency method then adjusted by employing a PSO algorithm. To evaluate the performance of the proposed controller, an experimental test bench has been built in laboratory using dSPACE1104 card. The WECS contains a wind turbine emulator and Permanent Magnet Synchronous Generator (PMSG) feed a nonlinear load and been connected to the grid via back-to-back converters. The experimental results demonstrate the superiority of the proposed controller over integer order controllers in steady and transient states by realizing maximum power extraction and improving the grid-side power factor. Keywords: wind turbine emulator; PMSG; hybrid fractional controller; dSPACE1104; PSO algorithm; grid connected. A comparative study between methods of detection and localization of open-circuit faults in a three phase voltage inverter fed induction motorby Cherif Bilal Djamal Eddine, Bendiabdellah Azeddine, Bendjebbar Mokhtar, Telli Abderrahim Abstract: The present paper work is focusing on the techniques of detection and localization of open-circuit faults in a three phase voltage source inverter fed induction motor. First, the paper starts by presenting the impact of an inverter IGBT open-circuit fault on the induction machine performance. A comparative study is then carried out between three different detection techniques: The mean value of the currents method, the measurement of the current drop method and the Park’s vectors method. The comparison is to assess each technique in terms of its performance that is the time detection rapidity and localization ability as well as in terms of hardware that is the number of current sensors required for IGBT open-circuit fault detection. To validate these methods, a test-rig is developed in our diagnostic group laboratory which consists of the realization of a two-level voltage source inverter controlled by a DSPACE-1104 Card to generate the PWM vector control for the induction motor. The obtained simulation and experimental results illustrate well the detection effectiveness of each technique as well as the comparison study merits. Keywords: detection; localization; open circuit; two-level inverter; DSPACE; induction motor. Robust Fuzzy Sliding Mode Control For Air Supply on PEM Fuel Cell Systemby Zakaria Baroud, Atallah Benalia, Carlos Ocampo-Martinez Abstract: In this paper, an adaptive fuzzy sliding mode controller is employed for air supply on Proton Exchange Membrane fuel cell (PEMFC) systems. The control objective is to adjust the oxygen excess ratio at a given setpoint in order to prevent oxygen starvation and damage of the fuel-cell stack. The proposed control scheme consists of two parts: a sliding mode controller (SMC) and fuzzy logic controller (FLC) with an adjustable gain factor, the SMC is used to calculate the equivalent control law and the FLC is used to approximate the control hitting law. The performance of the proposed control strategy is analyzed through simulations for different load variations. The results indicated that the adaptive fuzzy sliding mode controller (AFSMC) is excellent in terms of stability and several key performance indices such as the Integral Squared Error (ISE), the Integral Absolute Error (IAE) and the Integral Time-weighted Absolute Error (ITAE), as well as the settling and rise time for the closed-loop control system. Keywords: PEM Fuel Cell System; Oxygen Starvation; Sliding Mode Control; Fuzzy Logic Control; Stability Analysis. Hilbert Huang Transform and Pattern Recognition to detect defects in induction motorby NASSIMA HAMDAD, KAMAL HAMMOUCHE Abstract: In this paper, a new time-frequency analysis technique called Hilbert Huang Transform is applied to detect bars and ring defects in induction motor. A pattern recognition method called Support Vector Machine is used to classify the different operating modes of the motor (healthy and / or defective). The aim of this study is to improve the classification results obtained using the Fourier Transform (as frequency analysis technique) and temporal signals. Keywords: Hilbert Huang Transform (HHT), Empirical Mode Decomposition (EMD), Intrinsic Mode Functions (IMF), Fourier Transform (FT), Fault Diagnostic, Support Vector Machine (SVM), Induction Motor.