2019年6月19日学术报告——Prof. Guoxiang Gu
报告题目：Kalman Consensus Filtering in the Presence of Data Packet Drops
报告人：Prof. Guoxiang Gu
Guoxiang Gu received his Ph.D. degree in electrical engineering from University of Minnesota, Minneapolis, Minnesota in 1988. From 1988 to 1990, he was with the Department of Electrical Engineering, Wright State University, Dayton, Ohio, as a Visiting Assistant Professor. Since 1990, he joined Louisiana State University (LSU), Baton Rouge, where he is currently a Professor of Electrical and Computer Engineering.
Prof. Gu’s research interests include networked feedback control, system identification, and statistical signal processing. He has published two books, over 70 archive journal papers and numerous book chapters and conference papers. He served as an associate editor for the IEEE Transactions on Automatic Control from 1999 to 2001, SIAM Journal on Control and Optimization from 2006 to 2009, and Automatica from 2006 to 2012. From January 2018, he began to serve as an associate editor for the IEEE Transactions on Automatic Control, is presently the F. Hugh Coughlin/CLECO Distinguished Professor of Electrical Engineering at LSU, and a Fellow of IEEE.
We study Kalman consensus filtering (KCF) over wireless sensor networks in the presence of data packet drops. The optimal estimator is derived, assuming the TCP-like protocol. The stationary Kalman filter minimizes the average error variance, designed by solving the stabilizing solution to the modified algebraic Riccati equation (MARE). The existence of the stabilizing solution to the MARE is analyzed, and an equivalent condition in terms of some simple LMIs is obtained. Finally the KCF is studied, and a necessary and sufficient condition is obtained for the MS stability of the KCF, illustrate by a numerical example from the literature.