Title :
Minimax filtering in the presence of parameter uncertainties
Author :
Beugnon, Céline ; Singh, Tarunraj
Author_Institution :
Dept. of Mech. & Aerosp. Eng., State Univ. of New York, Buffalo, NY, USA
Abstract :
A discrete time minimax filter is presented in the paper and its steady state performance is compared with the performance of other Kalman based filters. Given uncertainty in the system model, this filter is designed such that it minimizes the maximum value of the cost, i.e., the trace of the steady state estimation error covariance matrix, over the ranges of uncertainty. The existence of a saddle point is pointed out for uncertainties in the noise characteristics, but no longer exists for plant dynamics uncertainties
Keywords :
Kalman filters; covariance matrices; discrete time systems; filtering theory; state estimation; uncertain systems; discrete time minimax filter; minimax filtering; parameter uncertainties; saddle point; steady state estimation error covariance matrix; Aerodynamics; Costs; Covariance matrix; Estimation error; Filtering; Integrated circuit noise; Kalman filters; Minimax techniques; Steady-state; Uncertainty;
Conference_Titel :
American Control Conference, 2000. Proceedings of the 2000
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-5519-9
DOI :
10.1109/ACC.2000.876707
