Paper Info
Title
Fuzzy Adaptive Tracking Control for State Constraint Switched Stochastic Nonlinear Systems With Unstable Inverse Dynamics
Abstract
In this article, a novel fuzzy adaptive tracking control scheme is concerned for a class of stochastic state-constrained switched nonlinear systems. The considered stochastic switched nonlinear system contains unknown nonlinearities and unstable inverse dynamics. In the design process, first, fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear dynamics. Second, the stochastic barrier Lyapunov functions (BLFs) are constructed to deal with the state constraint problem. Then, an adaptive fuzzy state-feedback controller is designed by utilizing the It∧o lemma and average dwell time (ADT) approach, which can guarantee both the control system and unstable inverse dynamics to be bounded in probability and all the states cannot violate their constrained sets. Two simulation examples are provided to show the effectiveness of the proposed control approach.
Year
DOI
Venue
2021
10.1109/TSMC.2019.2956263
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Keywords
DocType
Volume
Average dwell time (ADT),fuzzy adaptive control,state constraints,stochastic switched nonlinear systems
Journal
51
Issue
ISSN
Citations 
9
2168-2216
2
PageRank 
References 
Authors
0.35
34
3
Name
Order
Citations
PageRank
Wu Wei120414.84
Yongming Li24931147.76
Shaocheng Tong38625289.74