AbstractA controllable networked system is steered from an initial state to the desired state with the help of a set of driver node'/> Identification of Optimal Set of Driver Nodes in Complex Networked Systems Using Region of Attraction
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Identification of Optimal Set of Driver Nodes in Complex Networked Systems Using Region of Attraction

机译:使用吸引区域的复杂网络系统中最佳驱动节点集的识别

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AbstractA controllable networked system is steered from an initial state to the desired state with the help of a set of driver nodes. The set of driver nodes used to control a networked system may not be unique. There exist multiple set of driver nodes which may be utilized to control the networked system. This is imperative to characterize these sets of driver nodes for identification of an optimal set of driver nodes. This paper presents mathematical formulation and two algorithms using the Region of Attraction (ROA) to identify an optimal set of driver nodes. Optimal set of driver nodes is identified to maximize the stability region. For any practical networked systems, driver node has limited actuating capacity, this paper consider this limitationa priori. The proposed mathematical formulation and algorithms are verified with the help of numerical examples using the MATLAB simulation. The proposed algorithms have been validated by applying on a robotic network.]]>
机译:<![cdata [ <标题>抽象 ara>可控网络系统在一组的帮助下从初始状态转向所需的状态驱动程序节点。用于控制网络系统的驱动程序节点集可能不是唯一的。存在多组驱动器节点,其可以用于控制网络系统。这是必须表征这些驱动程序节点的表征,以确定最佳的驱动程序节点。本文介绍了使用吸引力区域(ROA)的数学制定和两种算法来识别最佳的驱动器节点。识别出最佳的驱动器节点以最大化稳定区域。对于任何实用的网络系统,驱动程序节点具有有限的动力容量,本文认为此限制<重点类型=“斜体”>先验。利用MATLAB仿真,利用数值示例验证所提出的数学制定和算法。通过在机器人网络上申请,已经验证了所提出的算法。 ]]>

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