Open AccessCommand filter‐based adaptive fuzzy backstepping control for a class of switched non‐linear systems with input quantisation
Author(s) -
Huang Leitao,
Li Yongming,
Tong Shaocheng
Publication year - 2017
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2016.1639
Subject(s) - backstepping , control theory (sociology) , fuzzy logic , mathematics , observer (physics) , filter (signal processing) , fuzzy control system , convergence (economics) , tracking error , dwell time , lyapunov stability , bounded function , adaptive control , computer science , control (management) , artificial intelligence , computer vision , medicine , clinical psychology , mathematical analysis , physics , quantum mechanics , economic growth , economics
This study investigates the problem of adaptive fuzzy output feedback control for a class of switched uncertain non‐linear systems with input quantisation. The considered system contains unknown non‐linearities, the switching signals, hysteretic quantised input and immeasurable states. Fuzzy logic systems are used to approximate the unknown non‐linearities and a fuzzy switched state observer is designed to estimate the unmeasured states. The hysteretic quantised input is divided into two bounded non‐linear functions in the control design to avoid chattering problem. By incorporating command filter into the backstepping design procedure, a fuzzy adaptive control scheme is developed, which solves the ‘explosion of complexity’ problem in conventional backstepping control schemes. Finally, the stability of the closed loop and convergence of the tracking error are proved via average dwell time and multiple Lyapunov functions methods. The effectiveness of the proposed approach is verified by a numerical simulation example.