Time-Varying Sensor and Actuator Selection for Uncertain Cyber-Physical Systems
Time-Varying Sensor and Actuator Selection for Uncertain Cyber-Physical Systems
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DOI：
10.1109/tcns.2018.2873229
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发表时间：
2017-08
影响因子：
4.2
通讯作者：
A. Taha;Nikolaos Gatsis;T. Summers;Sebastian A. Nugroho
中科院分区：
文献类型：
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作者：
A. Taha;Nikolaos Gatsis;T. Summers;Sebastian A. Nugroho
针对不确定网络物理系统，提出了解决时变传感器和执行器(SAA)选择问题的方法。我们证明了许多用于优化各种控制和估计度量的SAA选择问题可以被假定为具有混合整数双线性矩阵不等式(MIBMI)的半定优化问题。虽然这类优化问题在计算上具有挑战性，但我们提出了直接处理MIBMI的容易处理的方法，提供了上下界，并为SAA选择提供了有效的启发式方法。上界和下界分别通过逐次凸逼近和半定规划松弛得到，并通过切片算法从有界问题的解中选择。为了进行比较，还针对一大类系统开发了定制的分枝定界方法和组合贪婪方法。最后，进行了全面的数值仿真，比较了不同方法的优劣，说明了它们的有效性。
We propose methods to solve time-varying, sensor and actuator (SaA) selection problems for uncertain cyber-physical systems. We show that many SaA selection problems for optimizing a variety of control and estimation metrics can be posed as semidefinite optimization problems with mixed-integer bilinear matrix inequalities (MIBMIs). Although this class of optimization problems is computationally challenging, we present tractable approaches that directly tackle MIBMIs, providing both upper and lower bounds, and that lead to effective heuristics for SaA selection. The upper and lower bounds are obtained via successive convex approximations and semidefinite programming relaxations, respectively, and selections are obtained with a slicing algorithm from the solutions of the bounding problems. Custom branch-and-bound and combinatorial greedy approaches are also developed for a broad class of systems for comparison. Finally, comprehensive numerical simulations are performed to compare the different methods and illustrate their effectiveness.