Szczegóły publikacji
Opis bibliograficzny
A decentralized learning control scheme for constrained nonlinear interconnected systems based on dynamic event-triggered mechanism / Jing Wang, Jiacheng Wu, Hao Shen, Jinde Cao, Leszek RUTKOWSKI // IEEE Transactions on Systems, Man, and Cybernetics ; ISSN 2168-2216. Systems. — 2023 — vol. 53 iss. 8, s. 4934–4943. — Bibliogr. s. 4942–4943, Abstr. — Publikacja dostępna online od: 2023-03-30. — L. Rutkowski – dod. afiliacja: Systems Research Institute, Polish Academy of Sciences; Information Technology Institute, University of Social Sciences, Łódź
Autorzy (5)
- Wang Jing
- Wu Jiacheng
- Shen Hao
- Cao Jinde
- AGHRutkowski Leszek
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 150134 |
|---|---|
| Data dodania do BaDAP | 2023-11-15 |
| Tekst źródłowy | URL |
| DOI | 10.1109/TSMC.2023.3257871 |
| Rok publikacji | 2023 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | IEEE Transactions on Systems, Man, and Cybernetics, Systems |
Abstract
This article presents a decentralized learning control method for a class of partially unknown nonlinear systems with asymmetric control input constraints and mismatched interconnections via a novel dynamic event-triggering condition. By employing an integral reinforcement learning strategy, the system drift dynamics can be avoided in the learning process. Meanwhile, a critic neural network is designed to obtain the approximated value function and tuned by using the gradient descent approach. Furthermore, a novel dynamic event-triggering condition is designed to determine the occurrence of an event by introducing a dynamic variable. By using the Lyapunov theory, all signals in the closed-loop system are proved to be uniformly ultimately bounded. Finally, we present a nonlinear interconnected system and an interconnected power system to verify the effectiveness of the proposed method.
