Distributed Data-Driven Iterative Learning Consensus Tracking for Nonlinear Discrete-Time Multiagent Systems
| Autor: | Xian Yu, Zhongsheng Hou, Marios M. Polycarpou |
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| Rok vydání: | 2022 |
| Předmět: |
Strongly connected component
Theoretical computer science Computer science Multi-agent system Iterative learning control Directed graph Computer Science Applications Computer Science::Multiagent Systems Discrete time and continuous time Control and Systems Engineering Control theory Linearization Electrical and Electronic Engineering Protocol (object-oriented programming) |
| Zdroj: | IEEE Transactions on Automatic Control. 67:3670-3677 |
| ISSN: | 2334-3303 0018-9286 |
| Popis: | In this paper, a data-driven distributed leader-follower iterative learning consensus tracking control approach is proposed for unknown repetitive nonlinear non-affine discrete-time multi-agent systems. The leader's command is only communicated to a subset of the following agents and each following agent exchanges information only with its neighbors under a directed graph. A local iterative learning consensus control protocol is designed using only local measurements communicated among neighboring agents without the availability of physical and structural information of each agent by virtue of the dynamic linearization method both on the agent and the ideal distributed learning controller along the iteration axis. The convergent consensus properties of the tracking errors along the iteration axis are rigorously established under the strongly connected iteration-independent and iteration-varying communication topologies. One example is provided to validate the effectiveness of the proposed iterative learning consensus control protocol. |
| Databáze: | OpenAIRE |
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