TY - JOUR
T1 - Game theory approach to state estimation of linear discrete-time processes and its relation to H∞ -optimal estimation
AU - Yaesh, I.
AU - Shaked, U.
N1 - Funding Information:
This work was supported by the Cella and Marcos Maus Chair of Computer Systems Engineering at Tel-Aviv University.
PY - 1992/6
Y1 - 1992/6
N2 - A game theory approach to the state-estimation of linear discrete-time systems is presented. The resulting state estimation suggests an alternative to the Kalman filter, in cases where the exact statistics of the input and the measurement noise processes is not known. It turns out that the game-theoretic filter provides an H∞-optimal estimation. Moreover, it is shown that the covariance matrix of the estimation error is bounded, from above, by the solution of a modified Riccati equation.
AB - A game theory approach to the state-estimation of linear discrete-time systems is presented. The resulting state estimation suggests an alternative to the Kalman filter, in cases where the exact statistics of the input and the measurement noise processes is not known. It turns out that the game-theoretic filter provides an H∞-optimal estimation. Moreover, it is shown that the covariance matrix of the estimation error is bounded, from above, by the solution of a modified Riccati equation.
UR - http://www.scopus.com/inward/record.url?scp=0026880211&partnerID=8YFLogxK
U2 - 10.1080/00207179208934293
DO - 10.1080/00207179208934293
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AN - SCOPUS:0026880211
SN - 0020-7179
VL - 55
SP - 1443
EP - 1452
JO - International Journal of Control
JF - International Journal of Control
IS - 6
ER -
