Sensor Selection for Remote State Estimation with QoS Requirement Constraints

Huiwen Yang, Lingying Huang, Chao Yang, Yilin Mo, Ling Shi
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Abstract

In this paper, we study the sensor selection problem for remote state estimation under the Quality-of-Service (QoS) requirement constraints. Multiple sensors are employed to observe a linear time-invariant system, and their measurements should be transmitted to a remote estimator for state estimation. However, due to the limited communication resources and the QoS requirement constraints, only some of the sensors can be allowed to transmit their measurements. To estimate the system state as accurately as possible, it is essential to select sensors for transmission appropriately. We formulate the sensor selection problem as a non-convex optimization problem. It is difficult to solve such a problem and even to find a feasible solution. To obtain a solution which can achieve good estimation performance, we first reformulate and relax the formulated problem. Then, we propose an algorithm based on successive convex approximation (SCA) to solve the relaxed problem. By utilizing the solution of the relaxed problem, we propose a heuristic sensor selection algorithm which can provide a good suboptimal solution. Simulation results are presented to show the effectiveness of the proposed heuristic.
基于QoS需求约束的远程状态估计传感器选择
本文研究了在服务质量(QoS)需求约束下的远程状态估计传感器选择问题。对线性定常系统进行多传感器观测时,需要将测量结果传送给远程估计器进行状态估计。然而,由于通信资源有限和QoS要求的限制,只能允许部分传感器传输其测量值。为了尽可能准确地估计系统状态,选择合适的传感器进行传输是至关重要的。我们将传感器选择问题表述为一个非凸优化问题。这样的问题很难解决,甚至很难找到一个可行的解决方案。为了得到一个具有良好估计性能的解,我们首先对公式化问题进行了重新表述和松弛。然后,我们提出了一种基于连续凸逼近(SCA)的松弛问题求解算法。利用松弛问题的解,提出了一种启发式传感器选择算法,该算法能提供较好的次优解。仿真结果表明了所提启发式算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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