Nonlinear robust H-infinity filtering for a class of uncertain systems via convex optimization  

作　　者：Masoud ABBASZADEH Horacio J. MARQUEZ 

机构地区：[1]United Technologies Research Center,East Hartford,CT 06108,U.S.A. [2]Department of Electrical and Computer Engineering,University of Alberta,Edmonton,Alberta,Canada T6G 2V4

出　　处：《控制理论与应用（英文版）》2012年第2期152-158,共7页

基　　金：supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada

摘　　要：A new approach for robust H-infinity filtering for a class of Lipschitz nonlinear systems with time-varying uncertainties both in the linear and nonlinear parts of the system is proposed in an LMI framework. The admissible Lipschitz constant of the system and the disturbance attenuation level are maximized simultaneously through convex multi-objective optimization. The resulting H-infinity filter guarantees asymptotic stability of the estimation error dynamics with exponential convergence and is robust against nonlinear additive uncertainty and time-varying parametric uncertainties. Explicit bounds on the nonlinear uncertainty are derived based on norm-wise and element-wise robustness analysis.A new approach for robust H-infinity filtering for a class of Lipschitz nonlinear systems with time-varying uncertainties both in the linear and nonlinear parts of the system is proposed in an LMI framework. The admissible Lipschitz constant of the system and the disturbance attenuation level are maximized simultaneously through convex multi-objective optimization. The resulting H-infinity filter guarantees asymptotic stability of the estimation error dynamics with exponential convergence and is robust against nonlinear additive uncertainty and time-varying parametric uncertainties. Explicit bounds on the nonlinear uncertainty are derived based on norm-wise and element-wise robustness analysis.

关 键 词：Nonlinear uncertain systems Robust observers Nonlinear H-infinity filtering Convex optimization 

分 类 号：O231.2[理学—运筹学与控制论]