Fixed-Time Leader-Follower Consensus of Networked Nonlinear Systems via Event/Self-Triggered Control

This brief addresses the fixed-time event/self-triggered leader-follower consensus problems for networked multi-agent systems subject to nonlinear dynamics. First, we present an event-triggered control strategy to achieve the fixed-time consensus, and a new measurement error is designed to avoid Zen...

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Vydané v:IEEE transaction on neural networks and learning systems Ročník 31; číslo 11; s. 5029 - 5037
Hlavní autori: Liu, Jian, Zhang, Yanling, Yu, Yao, Sun, Changyin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.11.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Condition monitoring
Consensus algorithm
Dynamical systems
Error analysis
Fixed-time consensus tracking
Heuristic algorithms
Learning systems
Measurement errors
multi-agent system (MAS)
Multiagent systems
Nonlinear control
Nonlinear dynamics
Nonlinear systems
self-triggered control
Topology
ISSN:2162-237X, 2162-2388, 2162-2388
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Shrnutí:This brief addresses the fixed-time event/self-triggered leader-follower consensus problems for networked multi-agent systems subject to nonlinear dynamics. First, we present an event-triggered control strategy to achieve the fixed-time consensus, and a new measurement error is designed to avoid Zeno behavior. Then, two new self-triggered control strategies are presented to avoid continuous triggering condition monitoring. Moreover, under the proposed self-triggered control strategies, a strictly positive minimal triggering interval of each follower is given to exclude Zeno behavior. Compared with the existing fixed-time event-triggered results, we propose two new self-triggered control strategies, and the nonlinear term is more general. Finally, the performances of the consensus tracking algorithms are illustrated by a simulation example.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2019.2957069