Title :
Robust nonfragile Kalman filtering for uncertain linear systems with estimator gain uncertainty
Author :
Yang, Guang-hong ; Wang, Jian Liang
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
fDate :
2/1/2001 12:00:00 AM
Abstract :
The note is concerned with the problem of a robust nonfragile Kalman filter design for a class of uncertain linear systems with norm-bounded uncertainties. The designed state estimator can tolerate multiplicative uncertainties in the state estimator gain matrix. The robust nonfragile state estimator designs are given in terms of solutions to algebraic Riccati equations. The designs guarantee known upper bounds on the steady-state error covariance. A numerical example is given to illustrate the results
Keywords :
Kalman filters; Riccati equations; filtering theory; linear systems; stability; state estimation; uncertain systems; algebraic Riccati equations; estimator gain uncertainty; multiplicative uncertainties; norm-bounded uncertainties; robust nonfragile Kalman filtering; steady-state error covariance; uncertain linear systems; Covariance matrix; Filtering; Kalman filters; Linear systems; Nonlinear filters; Riccati equations; Robustness; State estimation; Uncertainty; Upper bound;
Journal_Title :
Automatic Control, IEEE Transactions on