In this paper, we investigate the state estimation problem over multiple Markovian packet drop channels. In this problem setup, a remote estimator receives measurement data transmitted from multiple sensors over individual channels. By the method of Markovian jump linear systems, an optimal stationary estimator that minimizes the error variance in the steady state is obtained, based on the mean-square (MS) stabilizing solution to the coupled algebraic Riccati equations. An explicit necessary and sufficient condition is derived for the existence of the MS stabilizing solution, which coincides with that of the standard Kalman filter. More importantly, we provide a sufficient condition under which the MS detectability with multiple Markovian packet drop channels can be decoupled, and propose a locally optimal stationary estimator but computationally more tractable. Analytic sufficient and necessary MS detectability conditions are presented for the decoupled subsystems subsequently. Finally, numerical simulations are conducted to illustrate the results on the MS stabilizing solution, the MS detectability, and the performance of the optimal and locally optimal stationary estimators.
Power Scheduling of Kalman Filtering in Wireless Sensor Networks with Data Packet Drops
School of Automation, Beijing Institute of Technology（北京理工大学自动化学院）；Key Laboratory of Intelligent Control and Decision of Complex Systems（复杂系统智能控制与决策重点实验室）
Control over adversarial packet-dropping communication networks revisited
School of Engineering and IT, University of NSW at the Australian Defence Force Academy（新南威尔士大学澳大利亚国防军学院工程与信息学院）；Department of Aerospace Engineering, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校航空航天工程系）
Sparse Packetized Predictive Control for Networked Control over Erasure Channels
Graduate School of Informatics, Kyoto University（京都大学大学院信息学研究科）；School of Electrical Engineering & Computer Science, The University of Newcastle（纽卡斯尔大学电气与计算机工程学院）；Aalborg University（奥尔堡大学）
Controller-jammer game models of Denial of Service in control systems operating over packet-dropping links
School of Engineering and IT, University of NSW at the Australian Defence Force Academy（新南威尔士大学澳大利亚国防军学院工程与信息科技学院）；Department of Aerospace Engineering, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校航空航天工程系）
Sparse Representations for Packetized Predictive Networked Control
Graduate School of Informatics, Kyoto University（京都大学情报学研究科）；School of Electrical Engineering & Computer Science, The University of Newcastle（纽卡斯尔大学电气与计算机工程学院）
