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Mitigating the effects of sensor uncertainties in networked multiagent systems

机译:减轻网络多主体系统中传感器不确定性的影响

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Networked multiagent systems consist of interacting agents that locally exchange information, energy, or matter. Since they do not in general have a centralized entity to monitor the activity of each agent, resilient distributed control system design for networked multiagent systems is essential in providing high system performance, reliability, and operation in the presence of system uncertainties. An important class of such system uncertainties that can significantly deteriorate the achievable closed-loop system performance is sensor uncertainties, which can arise due to low sensor quality, sensor failure, sensor bias, or detrimental environmental conditions. This paper presents a novel distributed adaptive control architecture for networked multiagent systems to mitigate the effect of sensor uncertainties. Specifically, we consider agents having high-order, linear dynamics with agent interactions corrupted by unknown exogenous disturbances. We show that the proposed adaptive control architecture guarantees asymptotic stability of the closed-loop dynamical system when the exogenous disturbances are time-invariant and uniform ultimate boundedness when the exogenous disturbances are time-varying. A numerical example is provided to illustrate the efficacy of the proposed distributed adaptive control architecture.
机译:联网的多主体系统由交互的主体组成,这些主体在本地交换信息,能量或物质。由于它们通常没有集中的实体来监视每个代理的活动,因此网络多代理系统的弹性分布式控制系统设计对于在存在系统不确定性的情况下提供高系统性能,可靠性和操作至关重要。这类传感器不确定性的重要类别,可能会严重降低可达到的闭环系统性能,这是传感器不确定性的原因,这可能是由于传感器质量低,传感器故障,传感器偏置或不利的环境条件引起的。本文提出了一种用于网络多主体系统的新型分布式自适应控制架构,以减轻传感器不确定性的影响。具体来说,我们考虑具有高阶线性动力学的智能体,其智能体之间的相互作用会因未知的外源性干扰而破坏。我们表明,当外源扰动是时不变的时,所提出的自适应控制体系结构保证了闭环动力系统的渐近稳定性,而当外源扰动是时变时,则保证了一致的最终有界性。提供了一个数值示例来说明所提出的分布式自适应控制体系结构的功效。

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