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Distributed adaptive output consensus control of a class of heterogeneous multi-agent systems under switching directed topologies

机译:切换定向拓扑下一类异构多智能体系统的分布式自适应输出共识控制

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In this paper, we consider a leader-follower output consensus problem for a class of uncertain heterogeneous non-affine pure-feedback multi-agent systems (MASs) in the presence of time-delay items and input saturation restrictions under switching directed topologies. A distributed adaptive control scheme is constructed by combining Lyapunov-Krasovskii functionals, backstepping methods, neural networks (NNs), auxiliary systems, graph theory, the mean value theorem and the implicit function theory along with the dynamic surface control (DSC) technique. The key advantages of the designed control approach are that there is no requirement of precise knowledge about uncertain dynamics and time delay items of individual agents and the computational burden can drastically be reduced by employing the DSC technique. Also, norms of unknown weight of neural networks are estimated online instead of weight vectors themselves. In theory, it can be proven that the output signals of follower agents can synchronize with the leader's and all signals in the closed-loop system are cooperatively semiglobally uniformly ultimately bounded (CSUUB) by suitable choice of design parameters. Two simulation examples are presented to demonstrate the effectiveness of the proposed strategy. (C) 2016 Elsevier Inc. All rights reserved.
机译:在本文中,我们考虑一类不确定的异构非仿射纯反馈多主体系统(MAS)的前导跟随输出共识问题,该系统存在时滞项并且在切换定向拓扑下存在输入饱和约束。通过结合Lyapunov-Krasovskii泛函,反步法,神经网络(NNs),辅助系统,图论,均值定理和隐函数理论以及动态表面控制(DSC)技术,构建了分布式自适应控制方案。设计的控制方法的主要优点是,不需要精确的知识来了解不确定的动力学和单个代理的时延项,并且可以通过采用DSC技术来大大减少计算负担。同样,在线估计神经网络的权重未知,而不是权重向量本身。从理论上讲,可以证明跟随者代理的输出信号可以与领导者同步,并且通过适当选择设计参数,闭环系统中的所有信号都可以协同半全局一致地最终有界(CSUUB)。给出了两个仿真示例,以证明所提出策略的有效性。 (C)2016 Elsevier Inc.保留所有权利。

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