AI Article Synopsis
- - This paper introduces a new hierarchical control system aimed at improving the tracking abilities of multiple types of agents that work together, even when they can't communicate with the main leader agent.
- - A specialized observer is created to help each follower estimate the leader's state in real time, allowing them to effectively track the leader's movements without needing global information about the entire team.
- - The decentralized controller designed in this study offers flexibility, as it doesn't require prior knowledge of the follower's models or control policies, and simulations demonstrate the method's effectiveness compared to existing approaches.
Article Abstract
This paper presents a novel hierarchical control scheme for solving the data-driven optimal cooperative tracking control problem of heterogeneous multi-agent systems. Considering that followers cannot communicate with the leader, a prescribed-time fully distributed observer is devised to estimate the leader's state for each follower. Then, the data-driven decentralized controller is designed to ensure that the follower's output can track the leader's one. Compared with the existing results, the advantages of the designed distributed observer are that the prescribed convergence time is completely predetermined by the designer, and the design of the observer gain is independent of the global topology information. Besides, the advantages of the designed decentralized controller are that neither the follower's system model nor a known initial stabilizing control policy is required. Finally, simulation results exemplify the advantage of the proposed method.
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| http://dx.doi.org/10.1016/j.isatra.2024.08.026 | DOI Listing |
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