Adaptive Anti-Disturbance Bumpless Transfer Control for Switched Neural Network Systems With Its Application to Switched Circuit Model
Ying Zhao, Donghui Wu, Changyi Xu, Shuanghe Yu, Tianhe Liu, Dong Yang
Abstract
This article focuses on the adaptive anti-disturbance bumpless transfer (AADBT) control issue for the switched neural network systems (SNNSs) encountered by the unmeasurable neural network (NN) modeled disturbance and the measurable unmodeled disturbance through the multiple Lyapunov functions method. First, an adaptive regulator is set to appropriate the unknown parameter in the NN disturbance model. Then, an adaptive disturbance observer is built to estimate the NN modeling disturbance. Further, based on the adaptive regulator and disturbance observer, a switched controller and a state-relevant switching regulator are dual designed to compensate the influence of the NN modeled disturbance and alleviate the influence of the unmodeled disturbance with the jumps in the control input are reduced. Finally, the established control scheme is applied to the switched RLC circuit model, exhibiting the effectiveness of the control strategy.