Title :
Robust estimation for discrete-time linear systems
Author :
Mangoubi, R.S. ; Appleby, Brent D. ; Verghese, George C.
Author_Institution :
Div. of Control & Decision Syst., MIT, Cambridge, MA, USA
fDate :
29 June-1 July 1994
Abstract :
Finite-horizon estimators are derived for time-varying, discrete-time linear systems that are robust to a general class of modeling uncertainties. A game theoretic formulation is used to obtain equations for a class of estimators which include the H∞ and the H2 (Kalman filter) estimator, as well as filters which trade off these two norms. The solution is obtained in two stages, with each stage requiring the solution of a Riccati equation. The estimators, which have linear dynamics, guarantee a bound on the induced norm of the mapping from the input noise to the output estimation error for all admissible uncertainties.
Keywords :
Kalman filters; Riccati equations; discrete time systems; estimation theory; game theory; linear systems; time-varying systems; H∞ estimator; H2 estimator; Kalman filter; Riccati equation; finite-horizon estimators; game theoretic formulation; linear dynamics; robust estimation; time-varying discrete-time linear systems; Aerodynamics; Estimation error; Game theory; Laboratories; Linear systems; Noise robustness; Nonlinear filters; Riccati equations; Robust control; Uncertainty;
Conference_Titel :
American Control Conference, 1994
Print_ISBN :
0-7803-1783-1
DOI :
10.1109/ACC.1994.751821
