Paper Info
Title
Adaptive Fuzzy Control of Stochastic Nonstrict-Feedback Nonlinear Systems With Input Saturation.
Abstract
This paper studies an adaptive fuzzy tracking control problem for nonlinear stochastic systems with input saturation and nonstrict-feedback form. We use fuzzy logic systems to approximate unknown nonlinear functions. A novel approach is introduced to tackle unknown functions with nonstrict-feedback structure in the design process. By introducing an auxiliary system, the input saturation problem can be solved. Moreover, based on backstepping control design approach, a novel adaptive fuzzy tracking controller is designed to guarantee all signals in the closed-loop system to be bounded, and the system output can be driven to track the trajectory of a given reference signal. Finally, some simulation results are given to confirm the effectiveness of the proposed approach.
Year
DOI
Venue
2017
10.1109/TSMC.2016.2635678
IEEE Trans. Systems, Man, and Cybernetics: Systems
Keywords
Field
DocType
Nonlinear systems,Fuzzy control,Stochastic systems,Adaptive control,Automation,System performance
Neuro-fuzzy,Control theory,Mathematical optimization,Backstepping,Nonlinear system,Control theory,Computer science,Fuzzy logic,Adaptive neuro fuzzy inference system,Fuzzy control system,Adaptive control
Journal
Volume
Issue
ISSN
47
8
2168-2216
Citations 
PageRank 
References 
30
0.67
49
Authors
5
Name
Order
Citations
PageRank
Hongyi Li14084120.76
Lu Bai21343.99
Qi Zhou324010.20
Renquan Lu42228106.36
lijie wang554517.15