Title :
Game theory approach to optimal linear estimation in the minimum H∞-norm sense
Author :
Yaesh, I. ; Shaked, U.
Author_Institution :
Dept. of Electron. Syst., Tel-Aviv Univ., Ramat-Aviv, Israel
Abstract :
A game theory approach to optimal state estimation is presented. It is found that under certain conditions a min-max estimation is identical to the optimal estimation in the minimum H∞-norm sense. These conditions are similar to those obtained by M. Mintz (J. Optim. Theory Appl., vol.9, p.99-111, 1972), where the relationship between Kalman filtering and the min-max terminal state estimation has been explored. This new interpretation of H∞-optimal state estimation provides insight into the mechanism of H∞-optimal filtering
Keywords :
filtering and prediction theory; game theory; state estimation; H∞-optimal filtering; H∞-optimal state estimation; game theory; min-max estimation; minimum H∞-norm; optimal linear estimation; Additive noise; Estimation error; Filtering; Game theory; H infinity control; Kalman filters; Noise measurement; Riccati equations; State estimation; Transfer functions;
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
DOI :
10.1109/CDC.1989.70149
