Fuzzy Finite Time Control for Switched Systems via Adding a Barrier Power Integrator

This paper concentrates on the study of finite time control for nonlinear switched systems. Based on a newly introduced adding a barrier integrator technique, a novel adaptive fuzzy control strategy is proposed for a class of nonlinear switched systems. Compared with the existing adaptive control methods, the proposed method has several distinguishing features. Finite time control: the proposed adaptive control method can solve the exact finite time control problem for the stabilization and some types of tracking issues. Namely, the errors will converge to zero in finite time. For a general tracking problem, the practical finite time control can be achieved. More general systems: the proposed method is suitable for high order nonlinear switched systems with arbitrary switching and unknown control gains. Some strict assumptions on the system dynamics are relaxed. Full state constraints: the proposed method can be utilized to deal with the full state constraints problem. Simple controller structure: the “explosion of the complexity” in the backstepping design is avoided. Singularity free design: the singularity problem is carefully handled during the whole design procedure. Examples are presented to illustrate the effectiveness of the proposed method.

[1]  Zhengrong Xiang,et al.  Finite-time stabilization of switched stochastic nonlinear systems with mixed odd and even powers , 2016, Autom..

[2]  Gang Feng,et al.  Robust adaptive output feedback control to a class of non-triangular stochastic nonlinear systems , 2018, Autom..

[3]  Min Wang,et al.  Dynamic Learning From Adaptive Neural Control of Robot Manipulators With Prescribed Performance , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[4]  Shiqi Zheng,et al.  Adaptive speed control based on just-in-time learning technique for permanent magnet synchronous linear motor , 2013 .

[5]  Li Yu,et al.  Energy-Efficient Distributed Filtering in Sensor Networks: A Unified Switched System Approach. , 2017, IEEE transactions on cybernetics.

[6]  Shaocheng Tong,et al.  Command-Filtered-Based Fuzzy Adaptive Control Design for MIMO-Switched Nonstrict-Feedback Nonlinear Systems , 2017, IEEE Transactions on Fuzzy Systems.

[7]  Shaocheng Tong,et al.  Barrier Lyapunov Functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints , 2016, Autom..

[8]  Rui Wang,et al.  Fuzzy Tracking Control for Switched Uncertain Nonlinear Systems With Unstable Inverse Dynamics , 2018, IEEE Transactions on Fuzzy Systems.

[9]  Yongduan Song,et al.  Adaptive finite time coordinated consensus for high-order multi-agent systems: Adjustable fraction power feedback approach , 2016, Inf. Sci..

[10]  Ding Zhai,et al.  Switched Adaptive Fuzzy Tracking Control for a Class of Switched Nonlinear Systems Under Arbitrary Switching , 2018, IEEE Transactions on Fuzzy Systems.

[11]  Liang Liu,et al.  Adaptive tracking control for a class of uncertain switched nonlinear systems , 2015, Autom..

[12]  Shaocheng Tong,et al.  Adaptive control-based Barrier Lyapunov Functions for a class of stochastic nonlinear systems with full state constraints , 2018, Autom..

[13]  Guang-Hong Yang,et al.  Prescribed Performance Fault-Tolerant Control of Uncertain Nonlinear Systems With Unknown Control Directions , 2017, IEEE Transactions on Automatic Control.

[14]  Xin-Ping Guan,et al.  Leader-following consensus for a class of high-order nonlinear multi-agent systems , 2016, Autom..

[15]  Mahesh Viswanathan,et al.  Stability Analysis of Switched Linear Systems Defined by Regular Languages , 2017, IEEE Transactions on Automatic Control.

[16]  Shaocheng Tong,et al.  Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics , 2017, IEEE Transactions on Cybernetics.

[17]  Hak-Keung Lam,et al.  Stable and robust fuzzy control for uncertain nonlinear systems , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[18]  Ting Li,et al.  A new approach to fast global finite-time stabilization of high-order nonlinear system , 2017, Autom..

[19]  Reza Shahnazi,et al.  Fuzzy Adaptive Tracking Control of Constrained Nonlinear Switched Stochastic Pure-Feedback Systems , 2017, IEEE Transactions on Cybernetics.

[20]  Yongming Li,et al.  Adaptive output-feedback control design with prescribed performance for switched nonlinear systems , 2017, Autom..

[21]  Chong Lin,et al.  Finite-Time Adaptive Fuzzy Tracking Control Design for Nonlinear Systems , 2018, IEEE Transactions on Fuzzy Systems.

[22]  Chong Lin,et al.  Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure. , 2018, IEEE transactions on cybernetics.

[23]  Jinde Cao,et al.  Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching , 2016, IEEE Transactions on Cybernetics.

[24]  Xiaojie Su,et al.  Sliding Mode Control of Discrete-Time Switched Systems with Repeated Scalar Nonlinearities , 2017, IEEE Transactions on Automatic Control.

[25]  Yongcan Cao,et al.  Finite-Time Connectivity-Preserving Consensus of Networked Nonlinear Agents With Unknown Lipschitz Terms , 2016, IEEE Transactions on Automatic Control.

[26]  Hairong Dong,et al.  Robust Consensus of Nonlinear Multiagent Systems With Switching Topology and Bounded Noises , 2016, IEEE Transactions on Cybernetics.

[27]  Yugang Niu,et al.  Finite-time sliding mode control synthesis under explicit output constraint , 2016, Autom..

[28]  Petros A. Ioannou,et al.  Adaptive control tutorial , 2006, Advances in design and control.

[29]  Yongduan Song,et al.  Design of adaptive finite-time controllers for nonlinear uncertain systems based on given transient specifications , 2016, Autom..

[30]  Guo-Xing Wen,et al.  Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems , 2016, IEEE Transactions on Cybernetics.

[31]  Wei Wang,et al.  A PD-Like Protocol With a Time Delay to Average Consensus Control for Multi-Agent Systems Under an Arbitrarily Fast Switching Topology , 2017, IEEE Transactions on Cybernetics.

[32]  Yongduan Song,et al.  Time-varying feedback for regulation of normal-form nonlinear systems in prescribed finite time , 2017, Autom..

[33]  Peter Xiaoping Liu,et al.  Observer-Based Fuzzy Adaptive Output-Feedback Control of Stochastic Nonlinear Multiple Time-Delay Systems , 2017, IEEE Transactions on Cybernetics.

[34]  Gang Feng,et al.  Adaptive Output Regulation of Heterogeneous Multiagent Systems Under Markovian Switching Topologies , 2018, IEEE Transactions on Cybernetics.

[35]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..

[36]  Young Hoon Joo,et al.  Local stability analysis of continuous-time Takagi-Sugeno fuzzy systems: A fuzzy Lyapunov function approach , 2014, Inf. Sci..

[37]  Mien Van,et al.  Finite Time Fault Tolerant Control for Robot Manipulators Using Time Delay Estimation and Continuous Nonsingular Fast Terminal Sliding Mode Control. , 2017, IEEE transactions on cybernetics.

[38]  Chunjiang Qian,et al.  Smooth output feedback stabilization of a class of planar switched nonlinear systems under arbitrary switchings , 2017, Autom..

[39]  Stefan Preitl,et al.  Stability analysis and design of a class of MIMO fuzzy control systems , 2013, J. Intell. Fuzzy Syst..

[40]  Yiguang Hong,et al.  Adaptive finite-time control of nonlinear systems with parametric uncertainty , 2006, IEEE Transactions on Automatic Control.

[41]  D. Mayne Nonlinear and Adaptive Control Design [Book Review] , 1996, IEEE Transactions on Automatic Control.

[42]  Yan-Jun Liu,et al.  Adaptive Fuzzy Tracking Control Based Barrier Functions of Uncertain Nonlinear MIMO Systems With Full-State Constraints and Applications to Chemical Process , 2018, IEEE Transactions on Fuzzy Systems.

[43]  Zhongjiu Zheng,et al.  Adaptive Approximation-Based Regulation Control for a Class of Uncertain Nonlinear Systems Without Feedback Linearizability , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[44]  Zhengrong Xiang,et al.  Adaptive practical finite-time stabilization for switched nonlinear systems in pure-feedback form , 2017, J. Frankl. Inst..

[45]  Guangdeng Zong,et al.  Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems , 2017, IEEE Transactions on Cybernetics.

[46]  Shaocheng Tong,et al.  Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems , 2017, Autom..

[47]  Shiqi Zheng,et al.  Stable adaptive PI control for permanent magnet synchronous motor drive based on improved JITL technique. , 2013, ISA transactions.

[48]  Jun Zhao,et al.  Decentralized Adaptive Neural Output-Feedback DSC for Switched Large-Scale Nonlinear Systems , 2017, IEEE Transactions on Cybernetics.

[49]  Wei Lin,et al.  Non-Lipschitz continuous stabilizers for nonlinear systems with uncontrollable unstable linearization , 2001 .

[50]  Guosong Yang,et al.  Feedback Stabilization of Switched Linear Systems With Unknown Disturbances Under Data-Rate Constraints , 2018, IEEE Transactions on Automatic Control.