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Formation iterative learning control for multi-agent systems with higher-order dynamics

机译:具有高阶动态的多智能体系的形成迭代学习控制

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This paper is devoted to solving formation problems of multi-agent systems with higher-order dynamics. By using the iterative learning control (ILC) approaches, effective distributed algorithms are developed to enable all agents in directed graphs to achieve the desired relative formations perfectly over a finite-time interval. It is shown that the graph theory can be combined to develop conditions for both asymptotic stability and monotonic convergence of multi-agent formation ILC. Simulation results are finally given to verify our theoretical study.
机译:本文旨在解决具有高阶动态的多助理系统的形成问题。 通过使用迭代学习控制(ILC)方法,开发了有效的分布式算法,以使各种代理能够在有限时间间隔内完全实现所需的相对地层。 结果表明,图表理论可以组合起来为多元剂形成ILC的渐近稳定性和单调会聚的条件。 仿真结果终于验证了我们的理论研究。

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