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首页> 外文期刊>Control Theory & Applications, IET >Robust adaptive backstepping control for hierarchical multi-agent systems with signed weights and system uncertainties
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Robust adaptive backstepping control for hierarchical multi-agent systems with signed weights and system uncertainties

机译:具有权重和系统不确定性的分级多智能体系统的鲁棒自适应反推控制

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摘要

This study is concerned with the robust adaptive backstepping control for hierarchical multi-agent systems with signed weights and non-linear system uncertainties. The considered network model is divided into several levels, and the corresponding Laplacian matrix in each level may be non-positive definiteness due to the existence of signed weights, which can lead to the instability of the whole system. To solve this problem, two definitions on and are firstly introduced, and by combining with a novel graph theoretical result, an effective robust backstepping control scheme is then developed to ensure the stability of hierarchical multi-agent systems. In particular, this study is a generalisation of the prior works with non-negative weights. Finally, an example on hierarchical multi-vehicle systems is given to demonstrate the validity of the proposed method.
机译:这项研究与具有权重和非线性系统不确定性的分级多智能体系统的鲁棒自适应反推控制有关。所考虑的网络模型分为几个级别,并且每个级别中对应的拉普拉斯矩阵可能由于有符号权重的存在而为非正定性,这可能导致整个系统不稳定。为了解决这个问题,首先介绍了的两个定义,然后结合新颖的图论结果,提出了一种有效的鲁棒反推控制方案,以确保分层多智能体系统的稳定性。特别地,本研究是对具有非负权重的现有作品的概括。最后,以分层多车辆系统为例,证明了该方法的有效性。

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