Allocating Sensors and Actuators via Optimal Estimation and Control
Allocating Sensors and Actuators via Optimal Estimation and Control
复制标题
通过最优估计和控制分配传感器和执行器
DOI：
10.1109/tcst.2016.2575799
复制
发表时间：
2017
影响因子：
4.8
通讯作者：
Dariush Fooladivanda
中科院分区：
文献类型：
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作者：
Joshua A. Taylor;Natchanon Luangsomboon;Dariush Fooladivanda
我们考虑的问题规划的位置和大小的传感器和执行器，以实现最佳的动态性能。使用控制和凸优化的基本结果，我们制定混合整数半定规划的执行器的位置和大小，以获得最低成本的线性二次型调节器，和传感器的位置，以获得最低的误差卡尔曼滤波器。由于最优线性控制和估计的对偶性，这两个公式几乎是相同的。我们也提出了类似的问题，在可观性和可控性，从而导致较小的混合整数半定规划。由于混合整数半定规划还不是一个成熟的技术，我们还使用贪婪算法结合连续半定规划。该方法被证明在两个现代应用程序从电力系统：的位置和大小的能量存储的调节和位置的相量测量单元的估计。
We consider the problem of planning the location and size of sensors and actuators to achieve optimal dynamic performance. Using basic results from control and convex optimization, we formulate mixed-integer semidefinite programs for the actuator placement and sizing to obtain the linear quadratic regulator with the lowest cost, and the sensor placement to obtain the Kalman filter with the lowest error. The two formulations are nearly identical due to the duality of optimal linear control and estimation. We also pose similar problems in terms of observability and controllability, which result in smaller mixed-integer semidefinite programs. Since the mixed-integer semidefinite programing is not yet a mature technology, we also use greedy heuristics in conjunction with continuous semidefinite programming. The approach is demonstrated on two modern applications from power systems: the placement and sizing of energy storage for regulation and the placement of phasor measurement units for estimation.