Regular Papers

International Journal of Control, Automation and Systems 2022; 20(3): 897-908

Published online March 11, 2022

https://doi.org/10.1007/s12555-021-0192-z

© The International Journal of Control, Automation, and Systems

Distributed Repetitive Learning Consensus Control of Mixed-order Linear Periodic Parameterized Nonlinear Multi-agent Systems

Jiaxi Chen and Junmin Li*

Xidian University

Abstract

This paper studies the consensus of mixed-order unknown periodic time-vary parameterized nonlinear multi-agent systems over heterogeneous network topology. The follower is represented by a first-order or secondorder periodic parameterized dynamic system, and the leader is presented through a second-order dynamic system. For unknown leader dynamics and bounded input disturbances, a differential adaptive parameter learning law is designed. For unknown periodic time-varying parameters, a repetitive learning law is designed based on the design method of repeated learning. Based on Lyapunov-like stability theory and repetitive learning control method, a new repetitive learning controller is designed and a sufficient condition of consensus for the MAS is also given in this paper. Unlike some existing results, this study is a fully distributed result. Finally, a simulation example is given to verify the effectiveness of this study.

Keywords Adaptive control, mixed-order, multi-agent systems, repetitive learning, unknown periodic time-varying parameter.

Article

Regular Papers

International Journal of Control, Automation and Systems 2022; 20(3): 897-908

Published online March 1, 2022 https://doi.org/10.1007/s12555-021-0192-z

Copyright © The International Journal of Control, Automation, and Systems.

Distributed Repetitive Learning Consensus Control of Mixed-order Linear Periodic Parameterized Nonlinear Multi-agent Systems

Jiaxi Chen and Junmin Li*

Xidian University

Abstract

This paper studies the consensus of mixed-order unknown periodic time-vary parameterized nonlinear multi-agent systems over heterogeneous network topology. The follower is represented by a first-order or secondorder periodic parameterized dynamic system, and the leader is presented through a second-order dynamic system. For unknown leader dynamics and bounded input disturbances, a differential adaptive parameter learning law is designed. For unknown periodic time-varying parameters, a repetitive learning law is designed based on the design method of repeated learning. Based on Lyapunov-like stability theory and repetitive learning control method, a new repetitive learning controller is designed and a sufficient condition of consensus for the MAS is also given in this paper. Unlike some existing results, this study is a fully distributed result. Finally, a simulation example is given to verify the effectiveness of this study.

Keywords: Adaptive control, mixed-order, multi-agent systems, repetitive learning, unknown periodic time-varying parameter.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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eISSN 2005-4092
pISSN 1598-6446