System Transformation-Based Event-Triggered Fuzzy Control for State Constrained Nonlinear Systems With Unknown Control Directions

This paper focuses on the event-triggered (ET) fuzzy tracking control for uncertain state constrained strict-feedback systems with unknown control directions. A novel nonlinear transformed function is developed to transform the constrained system states into the counterpart without any constraints....

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE transactions on fuzzy systems Ročník 31; číslo 7; s. 1 - 14
Hlavní autoři: Wang, Lixue, Wang, Min, Meng, Wenchao
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.07.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Adaptation
Closed loops
Co-design
Constraints
Control systems
Control theory
Data communication
Event-triggered fuzzy control
full state constraints
Fuzzy control
Fuzzy logic
Load modeling
Neural networks
Nonlinear systems
nonlinear transformed function
Sampling error
Stochastic systems
strict-feedback systems
Time-varying systems
Tracking control
unknown control directions
ISSN:1063-6706, 1941-0034
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper focuses on the event-triggered (ET) fuzzy tracking control for uncertain state constrained strict-feedback systems with unknown control directions. A novel nonlinear transformed function is developed to transform the constrained system states into the counterpart without any constraints. An ingenious adaptation law is developed to co-design the control law and the ET rule, thereby effectively compensating the sampling error caused by the ET rule under unknown control directions. Based on the presented adaptation law and the Nussbaum gain technique, a novel ET fuzzy tracking control strategy is proposed, which can handle the situations with and without state constraints in a unified way without readjusting the control scheme. Subsequently, the nonlinear transformed function is extended to the time-varying state constraints, and the corresponding ET fuzzy control scheme is also modified to guarantee the closed-loop boundedness. The proposed two control strategies guarantee the satisfactory tracking performance, avoid the violation of the prescribed state constraints, and decrease the communication load effectively. Finally, the usefulness of the developed methods is verified through two simulation examples.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2022.3224565