Author:
Zhang Yan,Luo Zijian,Xiong Wenjun
Abstract
Abstract
In this paper, we investigate the consensus problem of multi-agent systems with state constraints. To achieve the consensus effectively, the terminal iterative learning approach is proposed. This learning strategy is designed without the tracking error. And the consensus state is obtained by the the information interaction between agents. Meanwhile, the constraint condition holds in terms of our learning strategy. It shows the consensus conditions ensure the achievement of the constraints. Finally, a numerical simulation is given to illustrate the effectiveness of the main results.
Subject
General Physics and Astronomy
Cited by
1 articles.
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1. Distributed Terminal Iterative Learning Strategy for a Convex Optimization with Application to Resource Allocation;Proceedings of the 2022 3rd International Conference on Management Science and Engineering Management (ICMSEM 2022);2022-12-15