Observer-Based Event-Triggered Adaptive Fuzzy Control for Unmeasured Stochastic Nonlinear Systems With Unknown Control Directions

The issue of adaptive output-feedback stabilization is investigated for a category of stochastic nonstrict-feedback nonlinear systems subject to unmeasured state and unknown control directions. By combining the event-triggered mechanism and backstepping technology, an adaptive fuzzy output-feedback...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on cybernetics 2022-10, Vol.52 (10), p.10655-10666
Main Authors: Xia, Jianwei, Lian, Yuxiao, Su, Shun-Feng, Shen, Hao, Chen, Guoliang
Format: Article
Language:English
Subjects:
Actuators
Adaptive control
Control design
Control systems design
Event-triggered control
Feedback control
Fuzzy control
Fuzzy logic
Nonlinear systems
nonstrict-feedback
Observers
Output feedback
Process control
State observers
stochastic nonlinear systems
Stochastic systems
System effectiveness
unknown control directions
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The issue of adaptive output-feedback stabilization is investigated for a category of stochastic nonstrict-feedback nonlinear systems subject to unmeasured state and unknown control directions. By combining the event-triggered mechanism and backstepping technology, an adaptive fuzzy output-feedback controller is devised. In order to make the controller design feasible, a linear state transformation is introduced into the initial system. At the same time, the Nussbaum function technology is used to overcome the difficulties caused by unknown control directions, and the state observer solves the problem of the unmeasured state. Based on the fuzzy-logic system and its structural characteristics, the issue of unknown nonlinear function with nonstrict-feedback structure in the system is tackled. The designed controller could not only guarantee all signals of closed-loop systems are bounded in probability but also save communication resources effectively. Finally, numerical simulation and ship dynamics example are given to confirm the effectiveness of the proposed method.
ISSN:2168-2267
2168-2275
DOI:10.1109/TCYB.2021.3069853