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Networking improves robustness in flexible-joint multi-robot systems with only joint position measurements

机译:通过仅进行关节位置测量,网络可提高多关节柔性机器人系统的鲁棒性

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摘要

This paper studies the robustness in the coordination—via energy-shaping—of multiple nonidentical flexible-joint robots with only joint position measurements. The control objective is to drive all manipulators link positions to the same constant equilibrium. If the physical parameters are exactly known, then a classical decentralized energy-shaping controller solves the desired control objective. However, under parameter uncertainty, the globally asymptotically stable equilibrium point is shifted away from the desired value. The main contribution of the paper is to show that the steady-state performance is improved adding to the decentralized control policy information exchange between the agents. More precisely, it is proven that the equilibrium with the networked controller is always closer (in a suitable metric) to the desired one than that using the decentralized controller, provided the communication graph representing the network is undirected and connected. This result holds globally for sufficiently large interconnection gains and locally (in a suitably defined sense) for all values of the gains. An additional advantage of networking is that the asymptotic stabilization objective can be achieved injecting lower gains into the loop. The paper also provides simulation and experimental evidence, which illustrate the fact that networking improves robustness with respect to parameter uncertainty.
机译:本文研究了仅通过关节位置测量的多个不相同的柔性关节机器人在通过能量整形进行协调时的鲁棒性。控制目标是驱动所有机械手的连杆位置达到相同的恒定平衡。如果物理参数确切已知,则经典的分散式能量整形控制器可解决所需的控制目标。但是,在参数不确定性的情况下,全局渐近稳定的平衡点将偏离所需值。本文的主要贡献是表明,稳态性能得以改善,这增加了代理之间的分散控制策略信息交换。更精确地,已经证明,如果代表网络的通信图未定向和连接,则与使用分散控制器的平衡相比,与网络控制器的平衡总是更接近(以合适的度量)。对于足够大的互连增益,该结果在全局上适用;对于所有增益值,该结果在本地(在适当定义的意义上)适用。联网的另一个优点是可以实现渐近稳定化目标,将较低的增益注入环路。本文还提供了仿真和实验证据,它们说明了网络提高了参数不确定性方面的鲁棒性。

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