Iterative Inverse-Based Adaptive Fuzzy Control With Predetermined Tracking Accuracy for Hysteretic Nonlinear Systems
Guanyu Lai, Kai Huang, Yonghua Wang, Fang Wang, Hanzhen Xiao
Abstract
An inversion-based control strategy has been shown to be effective in compensating the hysteresis nonlinearities modeled by the Preisach operator. However, when the operator is coupled with the dynamics of uncertain nonlinear systems, there is still no result available for constructing the hysteresis inverse controller. To fill in the gap, in this study, we propose an iterative inverse-based adaptive fuzzy control scheme. Technically, an adaptive hysteresis inverse constructed through an iteration algorithm and updated by a projection-based adaptive law is developed as a feedforward hysteresis compensator, and then, the hysteresis inverse compensation error and plant nonlinearities and uncertainties are handled by a newly designed adaptive fuzzy controller. With our scheme, the closed-loop stability in the sense of signal boundedness, the prescribed steady-state tracking performance, and the convergence of the iteration algorithm can be established. Besides theoretical analysis, the effectiveness of our scheme is also validated by simulation and experimental results.