Prescribed Performance Bipartite Consensus Control for Stochastic Nonlinear Multiagent Systems Under Event-Triggered Strategy
| Autor: | Jiaang Zhang, Yong Guan, Chang-E. Ren |
|---|---|
| Rok vydání: | 2023 |
| Předmět: |
Lyapunov stability
Computer science Multi-agent system Computer Science Applications Term (time) Human-Computer Interaction Set (abstract data type) Nonlinear system Consensus Control and Systems Engineering Control theory Bounded function Bipartite graph Electrical and Electronic Engineering Software Information Systems |
| Zdroj: | IEEE Transactions on Cybernetics. 53:468-482 |
| ISSN: | 2168-2275 2168-2267 |
| DOI: | 10.1109/tcyb.2021.3119066 |
| Popis: | In this article, the event-triggered bipartite consensus problem for stochastic nonlinear multiagent systems (MASs) with unknown dead-zone input under the prescribed performance is studied. To surmount the influence of the dead-zone input, the dead-zone model is transformed into a linear term and a disturbance term. Meanwhile, the prescribed tracking performance is realized by developing a speed function, which means that all tracking errors of MASs can converge to a predefined set in a given finite time. Moreover, the unknown nonlinear dynamics are approximated by fuzzy-logic systems. By combining the dynamic surface approach and the Lyapunov stability theory, we design an adaptive event-triggered control algorithm, such that the bipartite consensus problem of stochastic nonlinear MASs can be achieved, and all signals are semiglobally uniformly ultimately bounded in probability of the closed-loop systems. Finally, simulation examples are proposed to verify the feasibility of the algorithm. |
| Databáze: | OpenAIRE |
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