一、主 题：Kalman Consensus Filtering in the Presence of Data Packet Drops
二、主讲人：Guoxiang Gu（IEEE Fellow, School of Electrical and Computer Engineering, Louisiana State University)
三、时 间：2019年5月16日 上午10:00-11:00
四、地 点：清水河校区 宾诺咖啡
五、主持人：自动化工程学院 胡江平 教授
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.
Guoxiang Gu (F’10) received the Ph.D. degree in electrical engineering from the University of Minnesota, Minneapolis, MN, USA, in 1988. From 1988 to 1990, he was with the Department of Electrical Engineering, Wright State University, Dayton, OH, as a Visiting Assistant Professor. In 1990, he joined Louisiana State University (LSU), Baton Rouge, where he is currently a Professor of Electrical and Computer Engineering. He has published two books, over 70 archive journal papers and numerous book chapters and conference papers. He has held visiting positions at Wright-Patterson Air Force Base and in the Hong Kong University of Science and Technology. His research interests include networked feedback control, system identification, and statistical signal processing. He was an Associate Editor for the SIAM Journal on Control and Optimization from 2006 to 2009, Automatica from 2006 to 2012, and has been serving as an Associate Editor for IEEE Transactions on Automatic Control since 2018, after his service from 1998 to 2000. He is presently the F. Hugh Coughlin/ CLECO Distinguished Professor of Electrical Engineering at LSU.
编辑：李果 / 审核：王晓刚 / 发布者：陈伟