Sparsity-Constrained Controllability Maximization With Application to Time-Varying Control Node Selection
Sparsity-Constrained Controllability Maximization With Application to Time-Varying Control Node Selection
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DOI：
10.1109/lcsys.2018.2833621
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发表时间：
2018-07-01
影响因子：
3
通讯作者：
Kashima, Kenji
中科院分区：
文献类型：
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作者：
Ikeda, Takuya;Kashima, Kenji
在这封信中，我们考虑的控制输入的L-0范数的约束下，可控性的定量度量的最大化。由于优化问题包含组合结构，为了减少计算负担，我们引入了一个凸松弛问题。我们证明了主要问题的解的存在性，并给出了一个简单的条件下，放松的问题给出了一个解决方案的主要问题。应该强调的是，主要问题可以制定时变控制节点的选择，试图提取何时何地外源输入应该提供，以实现高可控性的多智能体系统。
In this letter, we consider the maximization of a quantitative metric of controllability with a constraint of L-0 norm of the control input. Since the optimization problem contains a combinatorial structure, we introduce a convex relaxation problem for the sake of reducing computation burden. We prove the existence of solutions to the main problem and also give a simple condition under which the relaxed problem gives a solution to the main problem. It should be emphasized that the main problem can formulate time-varying control node selection, which attempts to extract when and where exogenous inputs should be provided in order to achieve high controllability of multi-agent systems.