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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

 

  • Designing Route Guidance Strategy with Travellers Stochastic Compliance: A Bi-level Optimal Control Procedure
    by Wei-li Sun, Ling-long Hu, Ping Li, Hui Wang 
    Keywords: .

  • Sparse parameter estimation of LTI models with l^p sparsity using genetic algorithm   Order a copy of this article
    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.

  • A new adaptive sliding mode control of nonlinear systems using Volterra series: application to hydraulic system   Order a copy of this article
    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.

  • Robust Q-parameterisation control for nonlinear magnetic bearing systems with imbalance based on TSK fuzzy model   Order a copy of this article
    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.

  • A sentiment analysis approach based on exploiting Chinese linguistic features and classification   Order a copy of this article
    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.

  • Small signal stability analysis and optimised control of a PMSG-based wind turbine using differential evolution   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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 Rectifiers
    by 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 Tracking
    by 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   Order a copy of this article
    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   Order a copy of this article
    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 Method
    by 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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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 decentralised sliding mode controller and observer for asynchronous nonlinear large scale systems with backlash   Order a copy of this article
    by Ahmad Taher Azar, Fernando E. Serrano 
    Abstract: In this article an adaptive decentralised sliding mode controller and observer for asynchronous nonlinear large scale systems with backlash are proposed. In the literature, only the synchronous case for input nonlinearities such as dead-zone and saturation are found. In this article, the asynchronous case for systems with backlash is studied considering the backlash effect. Owing to the complexity of the backlash nonlinearity, an adaptive decentralised controller is proposed because of the capability of this strategy to deal with uncertainties and to improve the system performance when this nonlinearity is found. Additionally, a decentralised sliding mode observer is proposed in order to estimate the states of the system.
    Keywords: decentralised control; switched systems; sliding mode control; 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 control
    by 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 linearization
    by 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 single support phase and double support phase   Order a copy of this article
    by Ravi Kumar Mandava, Pandu Ranga Vundavilli 
    Abstract: The present work explains the dynamically balanced gait generation of a 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, LagrangeEuler 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 a 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 non-singular fast terminal sliding mode control scheme for a class of nonlinear uncertain systems   Order a copy of this article
    by Beibei Zhang, Dongya Zhao 
    Abstract: In this paper, an adaptive second-order non-singular 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 non-singular 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 moves on a sliding surface. Then, an adaptive method are used to estimate the unknown upper bound of the lumped uncertainty caused by modelling error and external disturbance. The stability analysis of closed-loop system can be demonstrated by constructing a Lyapunov candidate function. Finally, the simulation results verify the effectiveness of the proposed control scheme.
    Keywords: non-singular 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 systems   Order a copy of this article
    by 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 a fault occurs, the fault itself cannot be compensated in the first subsystem, and a model predictive controller is designed in the second subsystem to compensate the fault, making the post-fault output PDF still track the desired PDF as closely as possible. A simulated example is given and desired results have been obtained.
    Keywords: stochastic distribution collaborative control systems; fault diagnosis; fault-tolerant control; model predictive control; linear matrix inequality.

  • Bolt quality testing research using weighted fusion algorithm based on correlation function   Order a copy of this article
    by Xiaoyun Sun, Hui Xing, Guang Han, Jiulong Cheng, Yongbang Yuan, Jianpeng Bian, Haiqing Zheng, Mingming Wang 
    Abstract: Bolt length is an important factor for the quality evaluation of anchors. 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, a 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; non-destructive testing; D-S fusion algorithm; Weighted fusion based on correlation function.

  • A new type-2 fuzzy modelling and identification for electrophysiological signals: a comparison between PSO, BBO, FA and GA approaches   Order a copy of this article
    by Mohammed Assam Ouali, Mouna Ghanai, Kheireddine Chafaa 
    Abstract: In this investigation, a novel type-2 fuzzy model for electrophysiological signals is presented. It is based on interval type-2 fuzzy systems. The proposed method can deal with the curve fitting and computational time problems of type-2 fuzzy systems. This approach will significantly reduce the number of type-2 fuzzy rules and simultaneously preserve the fitting quality. The proposed model comprises a parallel interconnection of two type-2 sub-fuzzy models. The first sub-fuzzy model is the primary model, which represents an ordinary model with a low resolution for the electrophysiological signal under consideration. To overcome the resolution quality problem and obtain a model with higher resolution, we introduce a second fuzzy sub-model called the error model, which represents a model for error modelling between the primary model and the real signal. The error model represents uncertainty in the primary model; this uncertainty is minimised by a simple subtraction of the error model output from the primary model output, resulting in a parallel interconnection between the two submodels; thus, a unique, entire final model possessing higher resolution is realised. The model's representation and identification are implemented by using type-2 fuzzy autoregressive (T2FAR) and type-2 fuzzy autoregressive moving average (T2FARMA) models. Identification is achieved by innovative metaheuristic optimisation algorithms, such as firefly and biogeography-based optimisation. The effectiveness of the method is evaluated through testing on generated synthetic ECG and also on real ECG signals taken from the MIT-BIH database. In addition, a detailed comparative study with several benchmark methods is given. Intensive computer experimentations confirm that the proposed method can significantly improve convergence, resolution and computational time.
    Keywords: electrophysiological signals; electrocardiogram; time series fitting; type-2 fuzzy logic; metaheuristics algorithms.

  • Model-based sliding functions design for sliding mode robot control   Order a copy of this article
    by Charles Fallaha, Maarouf Saad 
    Abstract: This paper introduces a novel manifold design for sliding mode control, applicable to second-order mechanical systems in which nonlinear dynamics can be formalised into that of robotic manipulators. The new approach shows that model-based sliding manifold design substantially simplifies the torque control law, which ultimately becomes linear in terms of joint angles and rates. Additionally, this approach allows the decoupling of the chattering effect on the torque inputs on each axis. A new property related to the gravity term is introduced, and is used for stability analysis and model validation. Simulation results compare the introduced approach with the conventional linear manifold design, and demonstrate that the new approach reduces transient constraints on torque input, and is more robust to matched uncertainties for low inertia robots.
    Keywords: sliding mode control; nonlinear control; robot control; nonlinear sliding manifolds; chattering.

  • High-performance torque controller design for AC driving 4WD electric vehicle in two timescales   Order a copy of this article
    by Bin Li, Zhijun Fu 
    Abstract: In this paper, a novel torque control method of AC induction motor in two timescales is proposed for 4WD electric vehicles. A two-timescale sliding-mode control (SMC) observer and a SMC controller are synthesised to ensure high-performance torque control. Two timescales are considered based on the natural timescale separation present in the AC induction motor driving system, i.e., rotor flux and speed corresponding to the slow dynamics, and the stator current corresponding to the fast dynamics. The convergence property of the controller is considered when performing the observer design rather than the conventional control method, in which the controller and observer are designed separately. Moreover, the more advanced space vector modulation (SVM) technology instead of the sinusoidal pulse width modulation (SPWM) method used in the conventional SMC is also introduced in the proposed method to achieve minimum torque ripple. The effectiveness of the proposed torque control method is illustrated through acting on a 4WD electric vehicle. Simulation results illustrate the improved performance compared with the conventional SMC method
    Keywords: torque control; 4WD; two timescales; electric vehicle; AC induction motor.

  • Command filter-based adaptive neural control for permanent magnet synchronous motor stochastic nonlinear systems with input saturation   Order a copy of this article
    by Yuxi Han, Jinpeng Yu, Zhen Liu, Lin Zhao 
    Abstract: For solving the problems of stochastic disturbance and input saturation in permanent magnet synchronous motors (PMSMs) drive systems, a command filter-based adaptive neural control method is proposed in this paper. Firstly, the neural networks technique is used to approximate unknown nonlinear functions. Then, the command filtered controller is constructed to avoid the "explosion of complexity" inherent in the classic backstepping control, and the error compensation mechanism is introduced to reduce the error caused by command filter. Moreover, the adaptive backstepping method is used to design controllers to ensure that all signals are bounded in the closed-loop systems. Finally, the effectiveness of the approach is certified by the given simulation results.
    Keywords: adaptive neural control; backstepping; PMSMs; command filter; stochastic nonlinear systems.

  • A Non-Linear Coupled-Variables Model for Mass Transfer Modes in MIG-MAG Processes with Experimental Validation
    by Paulo Evald, Jusoan Mór, Rodrigo Azzolin, Silvia Botelho 
    Abstract: Welding processes have relevant importance in many areas of industry, especially in the manufacturing area. The choice of mass transfer mode, to weld metal plates, depends on workpiece structure and its sensibility to the heat input and necessity for material deposition rate. Then, aiming the mass transfer modes in MIG-MAG (Metal Inert Gas - Metal Active Gas) processes utilising pure CO2 as shielding gas, the objective of this paper is present a detailed mathematical modelling for globular and short-circuit transfer modes. The proposed models comprehend a large set of process dynamics, approximating the simulated dynamics very closely to the physical process, which give a high level of credibility for the models. Furthermore, simulations and experimental data are presented to corroborate the validation of both models.
    Keywords: Non-linear systems; Time-varying systems; Coupled-parameters systems; Uncertain systems; Gas metal arc welding process.

  • Robust flux observer and robust block controller design for interior permanent magnet synchronous motor under demagnetization fault
    by Sajjad Shoja-Majidabad, Yashar Zafari 
    Abstract: This paper deals with rotor flux-linkage estimation in interior permanent magnet synchronous motors. In most applications, the rotor flux is considered as a known constant. However, sharp transients, high loads and high temperatures may cause demagnetization which has dominant impact on the interior permanent magnet synchronous motor performance. As a result, estimating the rotor flux-linkage can be helpful to detect and manage demagnetization fault. To estimate the rotor flux-linkage, a novel integral terminal sliding mode observer is proposed. This fast and robust observer uses stator currents as state variables which can tolerate well against motor uncertainties. This observer can be used to detect or alarm demagnetization fault for practical applications. However, to keep the motor performance during the demagnetization fault, a sliding mode block control strategy is proposed for the interior permanent magnet synchronous motor for a first time. The suggested robust controller is composed of a speed control loop (outer-loop) and two stator currents control loops (inner-loops). Due to rotor saliency, maximum torque per ampere technique is applied for the designed control strategy to provide reference current. Practical stability of the proposed observer and controllers is achieved properly. Finally, comprehensive simulations are carried out to show the effectiveness of the proposed observer and controllers.
    Keywords: Interior permanent magnet synchronous motor, Integral terminal sliding mode observer, Sliding mode block control, Maximum torque per ampere, demagnetization fault.

  • MLNMF : Multi-Label Learning based on Non-negative Matrix Factorization
    by Yu Han, Cheng Shao, ShouTao Yang, WeiWei Deng 
    Abstract: Abstract—Multi-label learning deals with the problem where each instance is associated with a set of labels. The task is to predict the label sets of unseen instances through training the instances with known label sets. Existing approaches make predictions by learning from the distribution of multi-label instances. However, the direct relevance between features and labels has often been overlooked in the literature. In this paper, a multi-label learning approach named MLNMF is presented, which is derived from the traditional Nonnegative Matrix Factorization algorithm.In detail, first propose to generate a label probability predict model (LPPM) utilizing the NMF method to capture the direct relevance between features and labels. Then exploit the decision stump method to generate a classifier for each label. The proposed method is a first-order approach which assumes that each label is independent with each other.Comparedtothe existing approaches for multi-label learning, the proposed approach is advantageous which is able to explore the direct correlation between features and labels and the the operating efficiency is much higher than other algorithms. The experimental results on a total of 9 benchmark data sets illustrate the competitiveness of MLNMF against some wellestablished multi-label learning algorithms.
    Keywords: machine learning, multi-label learning, Non-negative Matrix Factorization

  • Nonlinear Modeling of Leader-Follower UAV Close Formation Flight with Dynamic Inversion based Control
    by Johnson Yohannan 
    Abstract: The nonlinear dynamic inversion control techniques are used in leader-follower UAV dynamics modeling considering new input variables in the present paper. Three separate DI controllers are developed for holding the velocity, heading and flight path angles of both UAVs in a synchronous manner. A numerical simulation is performed at the end for validating this formation control mission of multiple UAVs. The quantitative estimation of reduction in follower drag while in close formation flight is also calculated along with the controller design.
    Keywords: dynamic inversion;close formation flight; leader-follower; UAV; induced drag; non-linear control; heading angle; flight path angle; aerodynamic derivatives; up-wash

  • Robust speed control design for electric motors using the Kharitonov theorem and Genetic Algorithms: An experimental study
    by Ashraf Saleem, Hisham Soliman, Serein Al-Ratrout, Mahmoud Masoud 
    Abstract: Electric motor drives are subjected to severe oscillations that might cause motor shaft fatigue and consequent breakdown during system operation. In this paper, a design of robust proportional integral (PI) controller for induction motor (IM) drives is presented. Uncertainties due to different load conditions of the drive system is modelled by a transfer function with interval coefficients. Instead of stabilizing an infinite number of polynomials, the Kharitonov theorem is used to design a robust controller by simultaneous stabilization of only four polynomials. The controller parameters are optimized so that the maximum eigenvalue among the four polynomials is pushed to the left in the complex plane. This is accomplished using Genetic Algorithm (GA) optimization to achieve the maximum possible rapidity of the system. The proposed controller is tested experimentally using the Hardware-in-the-Loop (HIL) technique. The simulation and experimental results show the validity and effectiveness of the proposed controller as compared to the auto-tuned PID control at different loading conditions.
    Keywords: robust digital control, induction motors, Kharitonov theorem, system identification, model-based control

  • Identification of Rock Bolt Quality Based on Improved Probabilistic Neural Network
    by weiguo di, mingming wang, xiaoyun sun, fengning kang, hui xing, haiqing zheng, jianpeng bian 
    Abstract: Anchoring technology is widely used in slope, tunnels and underground engineering. However, the rock bolt quality is still a hot problem which is difficult to solve. Considering the shortcoming of pull-out testing, defect identification in a nondestructive way is necessary. In the paper, the signal decomposition is obtained by rock bolt quality detector and wavelet packet transform and energy feature is extracted; the normalized energy eigenvector is converted as input of probabilistic neural network (PNN); the smoothing factor in PNN is optimized based on particle swarm optimization algorithm and the defect identification rate of PNN is improved. With a higher accuracy than radial basis functions (RBF) neural network and PNN, the improved PNN can provide a reference for defect identification of rock bolt in engineering without destruction.
    Keywords: rock bolt; nondestructive testing; wavelet packet; probabilistic neural network; particle swarm optimization

  • Identification of Multi-delay Systems using Orthogonal Hybrid Functions (HF) in States Space Environment
    by Srimanti Roychoudhury, Anish Deb 
    Abstract: In this paper, a set of orthogonal hybrid functions (HF) is utilised for identification of non-homogeneous as well as homogeneous multi-delay systems. The HF set works with function samples and reconstructs a function in a piecewise linear manner. This reduces mean integral square error (MISE) and also, computational burden compared to other competitive methods like Walsh analysis, block pulse analysis etc. The presented technique uses a simple algorithm for time-delay system identification. After building up the theory, numerical examples are treated to identify both first and second order delay systems. The results obtained are highly reliable to prove the validity of the proposal.
    Keywords: Orthogonal hybrid functions; Multi-delay systems; State space; System identification.

  • Performances Comparison Between Ultra-Local Model Control, Integral Sliding Mode Control and PID Control for A Coupled Tanks System
    by Hajer Thabet, Mounir Ayadi, Frédéric Rotella 
    Abstract: This paper deals with the comparison of robust control approaches for the level water control of coupled tanks system. A new ultra-local model control (ULMC) approach leading to adaptive controller is proposed. The parameter identification of the ultra-local model is based on the algebraic derivation techniques. The main advantages of this control strategy are its simplicity and robustness. A comparison study with the integral sliding mode control (ISMC) approach is carried out. The perfect knowledge of the output variable degree, which is a standard assumption for sliding modes, is assumed here. The comparison of the simulation results for the proposed adaptive controller with the ISMC controller and the classical PID controller has a better performances in the presence of external perturbations and parameter uncertainties.
    Keywords: Ultra-local model control; Adaptive PID controller; Integral sliding mode control; Robustness; Coupled tanks system.

  • Modelling of the effect of interface morphology on hydrogen diffusion in a clad plate   Order a copy of this article
    by Muming Hao, Wenchun Jiang, Yucai Zhang, Yun Luo 
    Abstract: Clad plate has been widely used to fabricate the pressure vessels, but a lot of cracks have been found around the interface between the base metal and clad metal at the hydrogen-contained environment. This study examines the hydrogen diffusion in a clad metal. A finite element model is built to simulate the hydrogen diffusion in a clad plate during the shutdown, and the effect of interface morphology has been studied. It is shown that the hydrogen is diffused to the interface and the peak hydrogen concentration is shown in the interface of the clad metal side. The wave interface has a smaller hydrogen concentration than the straight line interface. With increased wavelength and amplitude, the hydrogen concentration is decreased. The hydrogen concentration is increased as the clad metal thickness decreases. When the base metal thickness is increased, the hydrogen concentration is increased.
    Keywords: clad plate; hydrogen diffusion; interfaces.

  • A new three-dimensional chaotic system with a cloud-shaped curve of equilibrium points, its circuit implementation and sound encryption
    by Sundarapandian Vaidyanathan, Aceng Sambas, Sezgin Kacar, Unal Cavusoglu 
    Abstract: In the chaos literature, significant attention has been paid to chaotic systems with uncountable equilibrium points such as chaotic systems with line equilibrium, curve equilibrium, etc. This paper reports a novel chaotic system with a cloud-shaped curve of equilibrium points with symmetry properties. A new control law for completely synchronising the new chaotic system with cloud-shaped equilibrium curve has been established via adaptive integral sliding mode control. Also, an electronic circuit implementation of the theoretical system is designed to check its feasibility. As an engineering application, new results are derived for sound encryption with the new chaotic system.
    Keywords: Chaos; chaotic systems; chaos synchronisation; sliding mode control; circuit implementation; chaos based encryption; sound encryption.

  • Accelerated Model Predictive Controller for Artificial Pancreas
    by Mohamed EL HACHIMI, Abdelhakim BALLOUK, Ilyas KHELAFA, Abdenasser BAGHDAD 
    Abstract: This work consists on a contribution to the Artificial Pancreas (AP)rndevelopment by introducing new techniques of control based on an acceleration ofrnreference tracking by using a variable penalization of the cost function instead ofrnfixed and arbitrary penalization, two new functions of the weighting factors arernintroduced in the formulation of the control algorithm. This method allows a rapidrnrejection of meal disturbance, a reduction of glucose peak and a complete avoidancernof hypoglycemia. The developed controller performances are evaluated in silico testrnwhich is equivalent to animal test using the UVa/Padova simulator.
    Keywords: Artificial Pancreas; reference tracking; weighting factors; control algorithm;rndisturbance; hypoglycaemia

  • Surface Reconstruction Algorithm Based-on Local Data Features
    by zhang kun, Qiao shiquan, Gao Kai 
    Abstract: With the development of reverse engineering device, the point cloud data, as a common and important form, is applied to the surface reconstruction domain, especially during the non-contacting measurement. The 3D scanner is the popular instrument for non-contacting measurement as well as the point data collection. Though, the raw point data is so large, scattered and unordered, the representation of point cloud and reconstruction surface are critical contents in reverse engineering system. This paper provides a new method to describe the point cloud data and proposed the GeoSurface algorithm to complete the surface reconstruction. Firstly, we redefine the the point cloud according to set theory. Secondly, based on the estimation of point cloud feature, the rule of neighbor relationship of data can be deduced. According to this rule, we adopt the KD-tree algorithm to complete data organization, and improve its searching approach. In addition, the GeoSurface algorithm is proposed in this paper. In this algorithm, the curvature and normal vector are used to estimate local surface features. The GeoSurface algorithm uses iterative technique to mesh the surface and uses the depth of KD-tree to control the parameters in the algorithm. At last, by using the existing experimental equipment, we verify the GeoSurface algorithm. We adopt three data sets in the experiment, which is collected from the Stanford 3D scanning repository and 3D laser operated by our lab . The experimental results show the GeoSurface algorithm is an effective algorithm and achieved better result in running time and quality of surface reconstruction compared to greedy and poisson reconstruction algorithm.
    Keywords: Point cloud, geometrical features, set theory, surface reconstruction, reverse engineering.

  • Multi-model approach for 2-DOF control of non-linear CSTR process
    by Dipti Tamboli, Rajan Chile 
    Abstract: This paper proposes a novel approach to examine the performance of non-linear Continuous Stirred Tank Reactor (CSTR) at large set point changes where a single model adaptive controller falls short. The efficient closed-loop performance is achieved through multiple models accompanied with a bank of pole placement controllers. To select the best controller at a particular operating point, several multi-model techniques based on different scheduling variables have been adapted. To avoid the multiple switching and discontinuity in switching, the global control signal is calculated by assigning certain weight to each controller. The advantages of proposed method are a satisfactory performance at an unstable operating point as well as at large set point changes with reduced number of models. The effectiveness of the scheme is evaluated and demonstrated through simulation results at different scenarios to achieve 2 DOF control. The comparative study between various techniques shows the superiority of gain scheduler designed on the reference signal for set point tracking and disturbance rejection to tackle the non-linearities of CSTR.
    Keywords: CSTR; RLS; Pole Placement; Multiple Models; Gain Scheduler

  • Parameter identification and optimisation for a class of fractional-order chaotic system with time delay   Order a copy of this article
    by Xiao Li, Fucai Liu 
    Abstract: The fractional-order chaotic systems have more complex dynamic characteristics than the integer-order chaotic systems, which can more reflect the physical properties of the actual system and more practical values, whereas it is difficult to control the synchronisation for fractional chaotic systems. Chaotic system identification is the basis of chaos control and performance analysis. In order to identify the parameters of the chaotic systems with time delay, a novel particle swarm optimisation with increasing inertia weight is proposed, and then the issue is settled by solving an optimisation problem. The identification of parameters mainly includes the system order, the time delay parameter, and the coefficient parameters. An estimation-correction algorithm based on linear interpolation method is used to solve the fractional-order delay differential equation. The Mackey-Glass chaotic system is conducted and comparisons with other two widely used particle swarm optimisations and the differential evolution algorithm indicate the effectiveness of the proposed method, the improvement in identification accuracy as well as convergence speed.
    Keywords: parameter identification; fractional order; particle swarm optimisation; chaotic system; time delay.

  • Dynamic model of bottom blown oxygen copper smelting process
    by Bin Wang, Zhuo Wang, Yang Jia, Haibin Yu 
    Abstract: The bottom blown oxygen copper smelting technology is a new copper concentrate smelting technology. However, in the actual production, it is difficult to measure some key parameters online such as the matte grade, slag Fe/SiO2, melt temperature, total level, and matte level. A dynamic model is established to predict these parameters online, and is verified using actual production data. The results show that the predicted data and measured data are close, which indicate that the model could effectively predict these key parameters online and be applied to the actual production.
    Keywords: Bottom blown oxygen copper smelting process, Dynamic model, Mass balance, Energy balance

  • Numerical Analysis of H-Infinity Filter for System Parameter Identification
    by Vassilios Tsachouridis 
    Abstract: The numerical analysis of the H-Infinity filter algorithm for system parameter identification is addressed in this paper. After presenting the filter under study and the convergence characteristics of the algorithm, a first order perturbation analysis is conducted. More specifically, norm-wise bounds are derived for the sensitivities, condition numbers, forward errors, backward errors and rounding errors of the iterative computational operations of thernalgorithm. Consequently, numerical stability and accuracy rules can be potentially composed as measures of algorithmic reliability and dynamical numerical performance. For exploring the impact of incorporating the specific algorithm dynamics in the numerical analysis, a similar framework is presented for the computed solutions irrespective of the used algorithm. The paper further exploits the application of the synthesised numerical analysis framework to parameter identification of linear state space systems. Finally some numerical examples are given for demonstration purposes.
    Keywords: H-Infinity Filter; Numerical Algorithms; Error Analysis; Perturbation Analysis

  • Wiener model of pressure management for water distribution network
    by Shaoyuan Li, Dongming Liu, Jing Wu 
    Abstract: In this paper, a Wiener model is established to express the nonlinear dynamic pressure management mechanism of water distribution network (WDN). The studied topology of WDN is pumped into a closed system with pressure control. The hydraulic element tank plays a key role, and the pressure management model can be divided into two parts according to the feature of the tank being the only dynamic hydraulic component in the whole WDN: the linear dynamic module is to reflect the relationship between the volume (or level) and the flow of inflow/outflow of the tank, and nonlinear static module is to reflect the relationship between the outflows of the tanks and the heads of the terminal consumed nodes, and the linear dynamic block is followed by the static nonlinear block. Moreover, the Wiener model established is compared to the real model in Environmental Protection Agency Network (EPANET), where same consumer heads of the same water distribution network is applied. The theoretical data calculated by the Wiener model are compared with the real data generated by EPANET to show the effectiveness of our proposed modelling method, where three difference scenarios are tested, that is, a WDN with weekday water demands, a WDN including holidays water demands, and a WDN with the consideration of pipeline ages. It can be found that the running situations of Wiener model are similar to that of actual operation in all of the three cases, which shows that the Wiener model of WDN we established in this paper is computationally efficient and highly accurate.
    Keywords: Water distribution network (WDN); Pressure Management; Wiener model; Linear dynamic; Nonlinear static.

Special Issue on: ICMIC 2015 Sliding Mode Control, Theory and Application

  • Distributed second order sliding mode control for networked robots synchronisation: theory and experimental results   Order a copy of this article
    by Yassine Bouteraa, Nabil Derbel 
    Abstract: The paper focuses on synchronisation and trajectory tracking problems. The main goal of the distributed strategy is to produce and maintain a common behaviour using only local information interactions. A combination of a trajectory tracking theory and a cross-coupling algorithms have been used to solve synchronisation 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 for 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.

  • Discrete time quasi-sliding mode control of nonlinear uncertain systems   Order a copy of this article
    by Ibtissem Bsili, Jalel Ghabi, Hassani Messaoud 
    Abstract: The control of nonlinear uncertain systems is still an open area of research, and sliding mode control (SMC) is one of the robust and effective methods to cope with uncertain conditions. In this paper, a new SMC 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 is designed using the above technique and 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 approach   Order a copy of this article
    by 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 systems   Order a copy of this article
    by 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 guarantee the stability of overall closed-loop systems and ensure 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 as another solution to avoid the problem of chattering effect. Simulation results demonstrate the efficacy of the proposed control methodology to stabilise 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 Uncertainties   Order a copy of this article
    by 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 systems. 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 with the P&O algorithm, the proposed methodology reduces the oscillations around the maximum power point and provides better performance proprieties. Also, the simulation 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 approach   Order a copy of this article
    by 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.

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 system   Order a copy of this article
    by Antar Beddar, Hacen Bouzekri 
    Abstract: This paper focuses on designing and real time implementation of Hybrid Fractional Order Controller (HFC) for a 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 motor   Order a copy of this article
    by Cherif Bilal Djamal Eddine, Bendiabdellah Azeddine, Bendjebbar Mokhtar, Telli Abderrahim 
    Abstract: This paper focuses on the techniques of detection and localisation of open-circuit faults in a three-phase voltage source inverter-fed induction motor. 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 Parks vectors method. The comparison is to assess each technique in terms of its performance that is the time detection rapidity and localisation 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 that consists of the realisation 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; localisation; open circuit; two-level inverter; DSPACE; induction motor.

  • PCB-planar transformers equivalent circuit model identification using genetic algorithm   Order a copy of this article
    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   Order a copy of this article
    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.

  • Robust fuzzy sliding mode control for air supply on PEM fuel cell system   Order a copy of this article
    by 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 to 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 analysed 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 motor   Order a copy of this article
    by 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 an 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; empirical mode decomposition; intrinsic mode functions; Fourier transform; fault diagnostic; support vector machine; induction motor.

  • Investigation of radio channel model in indoor environment at 60 GHz   Order a copy of this article
    by Tarik Zarrouk, Moussa El Yahyaoui, Ali El Moussati, Ahmed El Oualkadi 
    Abstract: This paper proposes a modelling approach of 60 GHz channel model and evaluates the performance of the IEEE 802.15.3c system. We have used the actual 60 GHz High Speed Interface Orthogonal Frequency Division Multiplexing (HSI-OFDM) system model of the IEEE 802.15.3c standard with the realistic 60 GHz channel model based on the Triple-S and Valenzuela (TSV) model. In this work, we aim to investigate the effect of small and large scale fading in indoor environment under Line-Of-Sight (LOS) and No-LOS (NLOS) scenarios. The performance is evaluated in terms of the Error Vector Magnitude (EVM) in function of the distance and Signal Noise Ratio (SNR). This investigation is done by using a co-simulation technique between MATLAB and ADS software. The simulation results show that the TSV channel model presents better performance than the Friis equation in indoor environment and under LOS and NLOS scenarios.
    Keywords: 60 GHz; IEEE 802.15.3c; TSV; EVM; small-scale fading; large-scale fading.

  • On lambda-matrices and their applications in MIMO control systems design   Order a copy of this article
    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.
    DOI: 10.1504/IJMIC.2017.10008337