Finite-Time Adaptive Fuzzy Control for MIMO Nonlinear Systems With Input Saturation via Improved Command-Filtered Backstepping

In this article, the problem of finite-time adaptive fuzzy tracking control for multi-input and multi-output (MIMO) nonlinear systems with input saturation is investigated. The new finite-time command filter is introduced for generating command signals and their derivatives to work out the matter of “explosion of complexity,” and the modified fractional power-based error compensation mechanism (ECM) serves as removing the effect of filter error. Then, the finite-time adaptive control scheme is established via the backstepping recursive design technique. It guarantees all the signals of the closed-loop system (CLS) are finite-time bounded while the output tracking errors are regulated to a sufficiently small neighborhood of the origin in finite time. Finally, the effectiveness of the proposed finite-time control scheme is verified by a numerical comparison example.

[1]  Hongjing Liang,et al.  Containment Control of Semi-Markovian Multiagent Systems With Switching Topologies , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[2]  Hak-Keung Lam,et al.  Fault Detection for Fuzzy Semi-Markov Jump Systems Based on Interval Type-2 Fuzzy Approach , 2020, IEEE Transactions on Fuzzy Systems.

[3]  Peter Xiaoping Liu,et al.  Adaptive Fuzzy Finite-Time Control of Nonlinear Systems With Actuator Faults , 2020, IEEE Transactions on Cybernetics.

[4]  Qi-Ming Sun,et al.  Multi-dimensional Taylor network modelling and optimal control of SISO nonlinear systems for tracking by output feedback , 2019, IMA J. Math. Control. Inf..

[5]  Chao Zhang,et al.  Multidimensional Taylor network adaptive control for MIMO time‐varying uncertain nonlinear systems with noises , 2019, International Journal of Robust and Nonlinear Control.

[6]  Jiao‐Jun Zhang,et al.  Prescribed performance adaptive neural output feedback dynamic surface control for a class of strict‐feedback uncertain nonlinear systems with full state constraints and unmodeled dynamics , 2019, International Journal of Robust and Nonlinear Control.

[7]  Yuan-Xin Li,et al.  Finite time command filtered adaptive fault tolerant control for a class of uncertain nonlinear systems , 2019, Autom..

[8]  Li Ma,et al.  Observer-based adaptive fuzzy tracking control of MIMO switched nonlinear systems preceded by unknown backlash-like hysteresis , 2019, Inf. Sci..

[9]  Jing Zhang,et al.  Finite-Time Adaptive Fuzzy Control for Nonlinear Systems With Full State Constraints , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[10]  Yang Liu,et al.  A Novel Finite-Time Adaptive Fuzzy Tracking Control Scheme for Nonstrict Feedback Systems , 2019, IEEE Transactions on Fuzzy Systems.

[11]  Hongyi Li,et al.  Adaptive finite-time tracking control of full state constrained nonlinear systems with dead-zone , 2019, Autom..

[12]  Shaocheng Tong,et al.  Finite-Time Adaptive Fuzzy Output Feedback Dynamic Surface Control for MIMO Nonstrict Feedback Systems , 2019, IEEE Transactions on Fuzzy Systems.

[13]  Lin Zhao,et al.  Adaptive Neural Consensus Tracking for Nonlinear Multiagent Systems Using Finite-Time Command Filtered Backstepping , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[14]  Huaguang Zhang,et al.  Neural Observer and Adaptive Neural Control Design for a Class of Nonlinear Systems , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[15]  Lin Zhao,et al.  Fuzzy Finite-Time Command Filtered Control of Nonlinear Systems With Input Saturation , 2018, IEEE Transactions on Cybernetics.

[16]  Peng Shi,et al.  Finite-time command filtered backstepping control for a class of nonlinear systems , 2018, Autom..

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

[18]  Bing Chen,et al.  Neural networks-based command filtering control of nonlinear systems with uncertain disturbance , 2018, Inf. Sci..

[19]  Xuehua Li,et al.  Adaptive finite-time tracking control of switched nonlinear systems , 2017, Inf. Sci..

[20]  Chong Lin,et al.  Command Filtering-Based Fuzzy Control for Nonlinear Systems With Saturation Input , 2017, IEEE Transactions on Cybernetics.

[21]  Lijie Wang,et al.  Adaptive Fuzzy Control of Nonlinear Systems With Unmodeled Dynamics and Input Saturation Using Small-Gain Approach , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

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

[23]  C. L. Philip Chen,et al.  Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[24]  Shaocheng Tong,et al.  Command filter-based adaptive fuzzy backstepping control for a class of switched nonlinear systems , 2017, Fuzzy Sets Syst..

[25]  Guangdeng Zong,et al.  Command Filter-Based Adaptive Neural Tracking Controller Design for Uncertain Switched Nonlinear Output-Constrained Systems , 2017, IEEE Transactions on Cybernetics.

[26]  Lu Bai,et al.  Adaptive Fuzzy Control of Stochastic Nonstrict-Feedback Nonlinear Systems With Input Saturation , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[27]  Shaocheng Tong,et al.  Hybrid Fuzzy Adaptive Output Feedback Control Design for Uncertain MIMO Nonlinear Systems With Time-Varying Delays and Input Saturation , 2016, IEEE Transactions on Fuzzy Systems.

[28]  F. Lewis,et al.  Distributed consensus tracking for non-linear multi-agent systems with input saturation: a command filtered backstepping approach , 2016 .

[29]  Changyin Sun,et al.  Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[30]  Mingyu Wang,et al.  Approximation-Based Adaptive Tracking Control for MIMO Nonlinear Systems With Input Saturation , 2015, IEEE Transactions on Cybernetics.

[31]  Peng Shi,et al.  Observer and Command-Filter-Based Adaptive Fuzzy Output Feedback Control of Uncertain Nonlinear Systems , 2015, IEEE Transactions on Industrial Electronics.

[32]  Peng Shi,et al.  Distributed command filtered backstepping consensus tracking control of nonlinear multiple-agent systems in strict-feedback form , 2015, Autom..

[33]  Shaocheng Tong,et al.  Adaptive fuzzy output-feedback control for output constrained nonlinear systems in the presence of input saturation , 2014, Fuzzy Sets Syst..

[34]  Hao Xu,et al.  Fixed Final Time Optimal Adaptive Control of Linear Discrete-Time Systems in Input-Output form , 2013, J. Artif. Intell. Soft Comput. Res..

[35]  Bing Chen,et al.  Robust Adaptive Fuzzy Tracking Control for Pure-Feedback Stochastic Nonlinear Systems With Input Constraints , 2013, IEEE Transactions on Cybernetics.

[36]  Jing Zhou,et al.  Robust Adaptive Control of Uncertain Nonlinear Systems in the Presence of Input Saturation and External Disturbance , 2011, IEEE Transactions on Automatic Control.

[37]  Marios M. Polycarpou,et al.  Command filtered adaptive backstepping , 2010, Proceedings of the 2010 American Control Conference.

[38]  Marios M. Polycarpou,et al.  Command filtered backstepping , 2009, 2008 American Control Conference.

[39]  Geng Yang,et al.  Finite-Time-Convergent Differentiator Based on Singular Perturbation Technique , 2007, IEEE Transactions on Automatic Control.

[40]  Wei Lin,et al.  Global finite-time stabilization of a class of uncertain nonlinear systems , 2005, Autom..

[41]  Wei Lin,et al.  A continuous feedback approach to global strong stabilization of nonlinear systems , 2001, IEEE Trans. Autom. Control..

[42]  Sarangapani Jagannathan,et al.  Adaptive Fuzzy Logic Control of Feedback Linearizable Discrete-time Dynamical Systems Under Persistence of Excitation , 1998, Autom..

[43]  Sarangapani Jagannathan Discrete-time fuzzy logic control of a mobile robot with an onboard manipulator , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[44]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control - design and stability analysis , 1994 .