Event-Triggered Fuzzy Bipartite Tracking Control for Network Systems Based on Distributed Reduced-Order Observers

This article studies the distributed observer-based event-triggered bipartite tracking control problem for stochastic nonlinear multiagent systems with input saturation. First, different from conventional observers, we construct a novel distributed reduced-order observer to estimate unknown states f...

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Vydáno v:IEEE transactions on fuzzy systems Ročník 29; číslo 6; s. 1601 - 1614
Hlavní autoři: Liang, Hongjing, Guo, Xiyue, Pan, Yingnan, Huang, Tingwen
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Bipartite tracking control
Control systems
Directed graphs
distributed reduced-order observer
Feedback control
Fuzzy control
Fuzzy logic
fuzzy logic systems (FLS)
Fuzzy systems
Multi-agent systems
Multiagent systems
network systems
Nonlinear systems
Observers
Stochastic processes
Stochastic systems
Tracking control
Tracking errors
ISSN:1063-6706, 1941-0034
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Shrnutí:This article studies the distributed observer-based event-triggered bipartite tracking control problem for stochastic nonlinear multiagent systems with input saturation. First, different from conventional observers, we construct a novel distributed reduced-order observer to estimate unknown states for the stochastic nonlinear systems. Then, an event-triggered mechanism with relative threshold is introduced to reduce the burden of communication. In addition, the bipartite tracking controller is proposed for stochastic multiagent systems by using fuzzy logic systems and the backstepping approach. Meanwhile, it is proved that the designed method can guarantee that all the signals in the closed-loop systems are bounded in probability, and the distributed consensus tracking errors can converge to a small neighborhood of the origin via the Lyapunov stability theory. Finally, a simulation example is given to prove the effectiveness of the designed scheme.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2020.2982618