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Synchronised tracking control of multi-agent system

机译:多主体系统的同步跟踪控制

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This study is concerned with the synchronised tracking control for multiple agents with high-order dynamics, whereas the desired trajectory is only available for a portion of the team members. Using the weighted average of the neighbours' states as the reference signal, adaptive neural network (NN) control is designed for each agent in both full-state and output feedback cases. It is proved that the adaptive NN control law guarantees that the tracking error of each agent converges to an adjustable neighbourhood of the origin for both cases although some of them do not access the desired trajectory directly. Two simulation examples are provided to demonstrate the performance of the proposed approaches.
机译:这项研究涉及具有高阶动力学的多个代理的同步跟踪控制,而所需的轨迹仅适用于部分团队成员。使用邻居状态的加权平均值作为参考信号,为全状态和输出反馈情况下的每个代理设计了自适应神经网络(NN)控制。证明了自适应神经网络控制法则保证了两种情况下每个智能体的跟踪误差都收敛到原点的可调整邻域,尽管其中一些不能直接访问所需的轨迹。提供了两个仿真示例来演示所提出方法的性能。

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