Distributed Coordination for a Class of High-Order Multiagent Systems Subject to Actuator Saturations by Iterative Learning Control

This paper investigates a distributed coordination control for a class of high-order uncertain multiagent systems. Under the framework of iterative learning control, a novel fully distributed learning protocol is devised for the coordination problem of MASs including time-varying parameter uncertain...

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Bibliographic Details
Published inComplexity (New York, N.Y.) Vol. 2022; no. 1
Main Authors Yang, Nana, Li, Suoping
Format Journal Article
LanguageEnglish
Published Hoboken Hindawi 2022
Hindawi Limited
Wiley
Subjects
Actuators
Algorithms
Coordination
Graph theory
Learning
Multiagent systems
Neural networks
Parameter uncertainty
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Summary:This paper investigates a distributed coordination control for a class of high-order uncertain multiagent systems. Under the framework of iterative learning control, a novel fully distributed learning protocol is devised for the coordination problem of MASs including time-varying parameter uncertainties as well as actuator saturations. Meanwhile, the learning updating laws of various parameters are proposed. Utilizing Lyapunov theory and combining with Graph theory, the proposed algorithm can make each follower track a leader completely over a limited time interval even though each follower is without knowing the dynamics of the leader. Moreover, the extension to formation control is made. The validity and feasibility of the algorithm are verified conclusively by two examples.
ISSN:1076-2787
1099-0526
DOI:10.1155/2022/4020266