Time-varying RBF Neural Network-based Controller Design for a Class of Time-varying Nonlinear Systems

doi:10.16182/j.issn1004731x.joss.23-FZ0796E

Abstract

Abstract:

Atime-varying RBF neural network with time-varying properties is firstly proposed, and its approximation theorem is obtained. For a class of nonlinear systems with non-parametric time-varying uncertainties, the proposed time-varying RBF neural network is used to approximate the time-varying uncertainties, and the controller is designed by making use of Lyapunov stability theory and adaptive iterative learning control techniques. We obtain the stability theorem of the designed controller. The simulation results verify the effectiveness of the time-varying neural network and the correctness of the controller design scheme.

Key words: time-varying nonlinearity, RBF neural network, iterative learning, adaptive control

CLC Number:

TP273

Li Jing, Zhang Taotao, Jin Kai, Yuan Shengzhi, Zha Zilong. Time-varying RBF Neural Network-based Controller Design for a Class of Time-varying Nonlinear Systems[J]. Journal of System Simulation, 2023, 35(10): 2223-2236.

Figures/Tables 6

References 18

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