WHITE NOISE ESTIMATION FOR DISCRETE-TIME SYSTEMS WITH RANDOM DELAY AND PACKET DROPOUT

作     者：WANG Wei HAN Chunyan HE Fang 

作者机构：School of Control Science and EngineeringShandong University School of Electrical EngineeringUniversity of Jinan 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2014年第27卷第3期

页      面：476-493页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by the National Nature Science Foundation of China under Grant Nos.61104050,61203029 the Natural Science Foundation of Shandong Province under Grant No.ZR2011FQ020 the Scientific Research Foundation for Outstanding Young Scientists of Shandong Province under Grant No.BS2013DX008 the Graduate Education Innovation Project of Shandong Province under Grant No.SDYC12006 the Ph.D.Foundation Program of University of Jinan under Grant No.XBS1044 

主　　题：Discrete-time system packet dropout random delay white-noise estimators. 

摘      要：This paper is concerned with the optimal and suboptimal deconvolution problems for discrete-time systems with random delayed observations. When the random delay is known online, i.e., time stamped, the random delayed system is reconstructed as an equivalent delay-free one by using measurement reorganization technique, and then an optimal input white noise estimator is presented based on the stochastic Kahnan filtering theory. However, tb_e optimal white-noise estimator is timevarying, stochastic, and doesn＇t converge to a steady state in general. Then an alternative suboptimal input white-noise estimator with deterministic gains is developed under a new criteria. The estimator gain and its respective error covariance-matrix information are derived based on a new suboptimal state estimator. It can be shown that the suboptimal input white-noise estimator converges to a steady-state one under appropriate assumptions.