Adaptive Finite-Time Command Filtered Controller Design for Nonlinear Systems With Output Constraints and Input Nonlinearities

被引:22
作者
Wang, Kun [1 ,2 ]
Liu, Xiaoping [2 ]
Jing, Yuanwei [1 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Lakehead Univ, Dept Elect Engn, Thunder Bay, ON P7B 5E1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Backstepping; Nonlinear systems; Adaptive systems; Time-varying systems; Artificial neural networks; MIMO communication; Complexity theory; Adaptive neural networks (NNs); barrier Lyapunov functions (BLF); command filtered backstepping; finite-time stability; input nonlinearities; BACKSTEPPING CONTROL DESIGN; BARRIER LYAPUNOV FUNCTIONS; DYNAMIC SURFACE CONTROL; TRACKING CONTROL; STATE CONSTRAINTS; FEEDBACK-SYSTEMS; DIFFERENTIATION; STABILIZATION;
D O I
10.1109/TNNLS.2021.3083800
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This work addresses a finite-time tracking control issue for a class of nonlinear systems with asymmetric time-varying output constraints and input nonlinearities. To guarantee the finite-time convergence of tracking errors, a novel finite-time command filtered backstepping approach is presented by using the command filtered backstepping technique, finite-time theory, and barrier Lyapunov functions. The newly proposed method can not only reduce the complexity of computation of the conventional backstepping control and compensate filtered errors caused by dynamic surface control but also can ensure that the output variables are restricted in compact bounding sets. Moreover, the proposed controller is applied to robot manipulator systems, which guarantees the practical boundedness of all the signals in the closed-loop system. Finally, the effectiveness and practicability of the developed control strategy are validated by a simulation example.
引用
收藏
页码:6893 / 6904
页数:12
相关论文
共 48 条
[1]   Robust adaptive dynamic surface back-stepping tracking control of high-order strict-feedback nonlinear systems via disturbance observer approach [J].
Aghababa, Mohammad Pourmahmood ;
Moradi, Sajad .
INTERNATIONAL JOURNAL OF CONTROL, 2021, 94 (09) :2479-2495
[2]   Finite-time stability of continuous autonomous systems [J].
Bhat, SP ;
Bernstein, DS .
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2000, 38 (03) :751-766
[3]   Direct adaptive fuzzy control for nonlinear systems with time-varying delays [J].
Chen, Bing ;
Liu, Xiaoping ;
Liu, Kefu ;
Shi, Peng ;
Lin, Chong .
INFORMATION SCIENCES, 2010, 180 (05) :776-792
[4]   Adaptive Fuzzy Practical Fixed-Time Tracking Control of Nonlinear Systems [J].
Chen, Ming ;
Wang, Huanqing ;
Liu, Xiaoping .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (03) :664-673
[5]   Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints [J].
Chen, Mou ;
Ge, Shuzhi Sam ;
Ren, Beibei .
AUTOMATICA, 2011, 47 (03) :452-465
[6]   Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities [J].
Chen, Mou ;
Ge, Shuzhi Sam ;
How, Bernard Voon Ee .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2010, 21 (05) :796-812
[7]   Command Filtered Adaptive Backstepping [J].
Dong, Wenjie ;
Farrell, Jay A. ;
Polycarpou, Marios M. ;
Djapic, Vladimir ;
Sharma, Manu .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2012, 20 (03) :566-580
[8]   Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints [J].
Edalati, L. ;
Sedigh, A. Khaki ;
Shooredeli, M. Aliyari ;
Moarefianpour, A. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2018, 100 :311-329
[9]   Command Filtered Backstepping [J].
Farrell, Jay A. ;
Polycarpou, Marios ;
Sharma, Manu ;
Dong, Wenjie .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2009, 54 (06) :1391-1395
[10]   Command-filtered fixed-time trajectory tracking control of surface vehicles based on a disturbance observer [J].
Gao, Zhenyu ;
Guo, Ge .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2019, 29 (13) :4348-4365