Adaptive Tracking Control for Output-Constrained Switched MIMO Pure-Feedback Nonlinear Systems with Input Saturation

In this paper, an adaptive neural tracking control scheme for a class of uncertain switched multi-input multi-output (MIMO) pure-feedback nonlinear systems is proposed. The considered MIMO pure-feedback nonlinear system contains input and output constraints, completely unknown nonlinear functions an...

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Bibliographic Details
Published inJournal of systems science and complexity Vol. 36; no. 3; pp. 960 - 984
Main Authors Zhang, Haoyan, Zhao, Xudong, Wang, Huanqing, Niu, Ben, Xu, Ning
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023
Springer Nature B.V
Subjects
Adaptive control
Closed loops
Complex Systems
Constraints
Control
Control methods
Disturbance observers
Feedback control
Liapunov functions
Mathematics
Mathematics and Statistics
Mathematics of Computing
MIMO (control systems)
Neural networks
Nonlinear systems
Nonlinearity
Operations Research/Decision Theory
Radial basis function
Reference signals
Statistics
Systems Theory
Tracking control
output constraints
Adaptive control
input saturation
switched MIMO pure-feedback nonlinear systems
neural networks
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Summary:In this paper, an adaptive neural tracking control scheme for a class of uncertain switched multi-input multi-output (MIMO) pure-feedback nonlinear systems is proposed. The considered MIMO pure-feedback nonlinear system contains input and output constraints, completely unknown nonlinear functions and time-varying external disturbances. The unknown nonlinear functions representing system uncertainties are identified via radial basis function neural networks (RBFNNs). Then, the Nussbaum function is utilized to deal with the nonlinearity issue caused by the input saturation. To prevent system outputs from violating prescribed constraints, the barrier Lyapunov functions (BLFs) are introduced. Also, a switched disturbance observer is designed to make the time-varying external disturbances estimable. Based on the backstepping recursive design technique and the Lyapunov stability theory, the developed control method is verified applicable to ensure the boundedness of all signals in the closed-loop system and make the system output track given reference signals well. Finally, a numerical simulation is given to demonstrate the effectiveness of the proposed control method.
ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-023-1455-y