Quasi-equality constrained risk-sensitive filtering for nonlinear discrete-time systems

作     者：Linfeng SHEN, Yan LIN School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China 

作者机构：School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing China 

出 版 物：《控制理论与应用（英文版）》 (Journal of Control Theory and Applications)

年 卷 期：2012年第10卷第2期

页      面：229-235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] 08[工学] 0714[理学-统计学（可授理学、经济学学位）] 081101[工学-控制理论与控制工程] 070103[理学-概率论与数理统计] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 0701[理学-数学] 

基　　金：supported by the National Natural Science Foundation of China (No. 60874044) the Doctoral Fundation of Ministry of Education(No. 20111102110006) 

主　　题：Optimal estimation Risk-sensitive filtering Constraints 

摘      要：More and more data fusion models contain state constraints with valuable information in the filtering process. In this study, an optimal filter of risk sensitive with quasi-equality constraints is formulated using the reference probability method. Through recursion processes of probability density acquired from the probability measure change, the derived algorithm is optimal in the sense of the risk sensitive parameter. The system and constraint models are Consistent in statistics. Simulation results show that it is more robust and efficient than projection filters for the worst-case of noises and model uncertainty.