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Affine Model
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Jianbin Qiu – One of the best experts on this subject based on the ideXlab platform.
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fuzzy Affine Model based output feedback dynamic sliding mode controller design of nonlinear systems
IEEE Transactions on Systems Man and Cybernetics, 2021Co-Authors: Jianbin Qiu, Hakkeung LamAbstract:This paper investigates the problem of output feedback sliding mode control (SMC) for a class of uncertain nonlinear systems through Takagi–Sugeno fuzzy Affine Models. By adopting a state-input augmentation method, a descriptor system is first constructed to characterize the dynamical properties of the sliding motion. Based on a common quadratic Lyapunov function and piecewise quadratic Lyapunov functions, sufficient conditions for asymptotic stabstability analysis of the sliding motion are obtained with some convexification techniques. An output feedback dynamic SMC design scheme is proposed to force the states of the resulting closed-loop system onto the sliding surface locally in finite time. Two simulation examples are finally shown to illustrate the effectiveness of the proposed approaches.
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Asynchronous Sampled-Data Filtering Design for Fuzzy-Affine–Model-Based Stochastic Nonlinear Systems.
IEEE transactions on cybernetics, 2020Co-Authors: Jianbin Qiu, Imre J. Rudas, Huijun GaoAbstract:This article studies the asynchronous sampled-data filtering design problem for Ito stochastic nonlinear systems via Takagi-Sugeno fuzzy-Affine Models. The sample-and-hold behavior of the measurement output is described by an input delay method. Based on a novel piecewise quadratic Lyapunov-Krasovskii functional, some new results on the asynchronous sampled-data filtering design are proposed through a linearization procedure by using some convexification techniques. Simulation studies are given to illustrate the effectiveness of the proposed method.
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fuzzy Affine Model based output feedback controller design for nonlinear impulsive systems
Communications in Nonlinear Science and Numerical Simulation, 2019Co-Authors: Heting Zhang, Jianbin QiuAbstract:Abstract This paper studies the robust output feedback control problem for a class of nonlinear systems with impulsive effects via T-S fuzzy Affine Models. By employing a state-input augmentation scheme, some new results on the piecewise Affine (PWA) output feedback controller synthesis for T-S fuzzy Affine impulsive systems are obtained through piecewise quadratic Lyapunov functions. Sufficient criteria for exponential stabstability analysis of the resulting closed-loop system are given within a convex optimization setup. A simulation example is shown to verify the effectiveness of the proposed approach.
Yanling Wei – One of the best experts on this subject based on the ideXlab platform.
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fuzzy Affine Model based memory filter design of nonlinear systems with time varying delay
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Yanling Wei, Jianbin Qiu, Hamid Reza KarimiAbstract:This paper studies the piecewise-Affine memory $\mathscr {H}_{\infty }$ filtering problem for nonlinear systems with time-varying delay in a delay-dependent framework. The nonlinear plant is characterized by a continuous-time Takagi–Sugeno fuzzy-Affine Model with parametric uncertainties. The purpose is to develop a new approach for filter synthesis procedure with less conservatism. Specifically, by constructing a novel Lyapunov–Krasovskii functional, together with a Wirtinger-based integral inequality, reciprocally convex inequality and S-procedure, an improved criterion is first attained for analyzing the $\mathscr {H}_{\infty }$ performance of the filtering error system, and then via some linearization techniques, the piecewise-Affine memory filter synthesis is carried out. It is shown that the existence of desired filter gains can be explicitly determined by the solution of a convex optimization problem. Finally, simulation studies are presented to reveal the effectiveness and less conservatism of the developed approaches. It is anticipated that the proposed scheme can be further extended to the analysis and synthesis of continuous-time fuzzy-Affine dynamic systems with integrated communication delays in the networked circumstance.
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approaches to t s fuzzy Affine Model based reliable output feedback control for nonlinear ito stochastic systems
IEEE Transactions on Fuzzy Systems, 2017Co-Authors: Yanling Wei, Jianbin Qiu, Hakkeung LamAbstract:This paper deals with the problem of reliable and robust $\mathscr {H}_{\infty }$ static output feedback (SOF) controller synthesis for continuous-time nonlinear stochastic systems with actuator faults. The nonlinear stochastic plant is expressed by an Ito-type Takagi–Sugeno fuzzy-Affine Model with parametric uncertainties, and a Markov process is employed to Model the occurrence of actuator fault. The purpose is to design an admissible piecewise SOF controller, such that the resulting closed-loop system is stochastically stable with a prescribed disturbance attenuation level in an $\mathscr {H}_{\infty }$ sense. Specifically, based on a Markovian Lyapunov function combined with Ito differential formula, S-procedure, and some matrix inequality convexification procedures, two new approaches to the reliable SOF controller analysis and synthesis are proposed for the underlying stochastic fuzzy-Affine systems. It is shown that the existence of desired reliable controllers is fully characterized in terms of strict linear matrix inequalities. Finally, simulation examples are presented to illustrate the effectiveness and advantages of the developed methods.
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fixed order piecewise Affine output feedback controller for fuzzy Affine Model based nonlinear systems with time varying delay
IEEE Transactions on Circuits and Systems I-regular Papers, 2017Co-Authors: Yanling Wei, Jianbin Qiu, Peng Shi, Mohammed ChadliAbstract:This paper studies the problem of delay-dependent fixed-order memory piecewise-Affine $\mathscr {H}_{\infty }$ output feedback control for a class of nonlinear systems with time-varying delay via a descriptor system approach. The nonlinear plant is expressed by a continuous-time Takagi-Sugeno (T-S) fuzzy-Affine Model. Specifically, by utilizing a descriptor Model transformation, the original closed-loop system is firstly reformulated into a descriptor system. Based on a new type of Lyapunov-Krasovskii functional (LKF), combined with a Wirtinger-based integral inequality, reciprocally convex inequality and S-procedure, a novel $\mathscr {H}_{\infty }$ performance analysis criterion is then derived for the underlying closed-loop system. Furthermore, by explicitly taking advantage of the redundancy of descriptor system formulation, together with a linearization procedure, the piecewise-Affine output feedback controller synthesis is carried out. It is shown that the desired fixed-order memory piecewise-Affine controllers with different structures can be established in a unified framework. Finally, simulation studies are presented to show the effectiveness and less conservatism of the proposed approaches.
H. Liu – One of the best experts on this subject based on the ideXlab platform.
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Piecewise Affine Model-based H ∞ static output feedback control of constrained non-linear processes
IET Control Theory & Applications, 2010Co-Authors: Jianbin Qiu, Gang Feng, Tao Zhang, H. LiuAbstract:This study develops two efficient static output feedback (SOF) control approaches for a class of constrained non-linear processes represented by uncertain piecewise Affine Models. The parameter uncertainties in the piecewise Affine Models are assumed to be time varying and norm bounded. With the aid of the congruence transformation, degenerate ellipsoids-based S-procedure, and some bounding inequalities, the piecewise SOF controller can be easily obtained by solving a convex semi-definite programming problem subject to some linear matrix inequalities. The resulting closed-loop system stability can be guaranteed as well as the H ∞ control performance, and the stabilising design is less conservative owing to the piecewise quadratic Lyapunov functions. The performance of the proposed control approaches are demonstrated by simulation results on a non-linear benchmark plant.
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piecewise Affine Model based h static output feedback control of constrained non linear processes
Iet Control Theory and Applications, 2010Co-Authors: Jianbin Qiu, Gang Feng, Tao Zhang, H. LiuAbstract:This study develops two efficient static output feedback (SOF) control approaches for a class of constrained non-linear processes represented by uncertain piecewise Affine Models. The parameter uncertainties in the piecewise Affine Models are assumed to be time varying and norm bounded. With the aid of the congruence transformation, degenerate ellipsoids-based S-procedure, and some bounding inequalities, the piecewise SOF controller can be easily obtained by solving a convex semi-definite programming problem subject to some linear matrix inequalities. The resulting closed-loop system stability can be guaranteed as well as the H ∞ control performance, and the stabilising design is less conservative owing to the piecewise quadratic Lyapunov functions. The performance of the proposed control approaches are demonstrated by simulation results on a non-linear benchmark plant.
Mohammed Chadli – One of the best experts on this subject based on the ideXlab platform.
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fixed order piecewise Affine output feedback controller for fuzzy Affine Model based nonlinear systems with time varying delay
IEEE Transactions on Circuits and Systems I-regular Papers, 2017Co-Authors: Yanling Wei, Jianbin Qiu, Peng Shi, Mohammed ChadliAbstract:This paper studies the problem of delay-dependent fixed-order memory piecewise-Affine $\mathscr {H}_{\infty }$ output feedback control for a class of nonlinear systems with time-varying delay via a descriptor system approach. The nonlinear plant is expressed by a continuous-time Takagi-Sugeno (T-S) fuzzy-Affine Model. Specifically, by utilizing a descriptor Model transformation, the original closed-loop system is firstly reformulated into a descriptor system. Based on a new type of Lyapunov-Krasovskii functional (LKF), combined with a Wirtinger-based integral inequality, reciprocally convex inequality and S-procedure, a novel $\mathscr {H}_{\infty }$ performance analysis criterion is then derived for the underlying closed-loop system. Furthermore, by explicitly taking advantage of the redundancy of descriptor system formulation, together with a linearization procedure, the piecewise-Affine output feedback controller synthesis is carried out. It is shown that the desired fixed-order memory piecewise-Affine controllers with different structures can be established in a unified framework. Finally, simulation studies are presented to show the effectiveness and less conservatism of the proposed approaches.
Gang Feng – One of the best experts on this subject based on the ideXlab platform.
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piecewise Affine Model based h static output feedback control of constrained non linear processes
Iet Control Theory and Applications, 2010Co-Authors: Jianbin Qiu, Gang Feng, Tao Zhang, H. LiuAbstract:This study develops two efficient static output feedback (SOF) control approaches for a class of constrained non-linear processes represented by uncertain piecewise Affine Models. The parameter uncertainties in the piecewise Affine Models are assumed to be time varying and norm bounded. With the aid of the congruence transformation, degenerate ellipsoids-based S-procedure, and some bounding inequalities, the piecewise SOF controller can be easily obtained by solving a convex semi-definite programming problem subject to some linear matrix inequalities. The resulting closed-loop system stability can be guaranteed as well as the H ∞ control performance, and the stabilising design is less conservative owing to the piecewise quadratic Lyapunov functions. The performance of the proposed control approaches are demonstrated by simulation results on a non-linear benchmark plant.
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Piecewise Affine Model-based H ∞ static output feedback control of constrained non-linear processes
IET Control Theory & Applications, 2010Co-Authors: Jianbin Qiu, Gang Feng, Tao Zhang, H. LiuAbstract:This study develops two efficient static output feedback (SOF) control approaches for a class of constrained non-linear processes represented by uncertain piecewise Affine Models. The parameter uncertainties in the piecewise Affine Models are assumed to be time varying and norm bounded. With the aid of the congruence transformation, degenerate ellipsoids-based S-procedure, and some bounding inequalities, the piecewise SOF controller can be easily obtained by solving a convex semi-definite programming problem subject to some linear matrix inequalities. The resulting closed-loop system stability can be guaranteed as well as the H ∞ control performance, and the stabilising design is less conservative owing to the piecewise quadratic Lyapunov functions. The performance of the proposed control approaches are demonstrated by simulation results on a non-linear benchmark plant.
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Robust Constrained Fuzzy Affine Model Predictive Control With Application to a Fluidized Bed Combustion Plant
IEEE Transactions on Control Systems Technology, 2008Co-Authors: Tiejun Zhang, Gang Feng, Wenguo XiangAbstract:In this paper, robust constrained Model predictive control of uncertain fuzzy Affine systems is considered. Based on piecewise quadratic Lyapunov functions, highly efficient robust constrained predictive control approaches are developed so that the closed-loop stability is guaranteed, and the transient control performance is improved even under input or state constraints. Moreover, by using approximate ellipsoid and S -procedure, the solution to the fuzzy Affine Model based predictive control can be cast as a convex optimization problem subject to some linear matrix inequalities, rather than a nonconvex problem via bilinear matrix inequalities as in conventional fuzzy Affine Model-based control. The proposed controllers are thus easier for real-time implementation in industry. Simulation results on the fluidized bed combustion plant have demonstrated the performance of the proposed approaches.