Title :
Model validation and state estimation for uncertain continuous-time systems with missing discrete-continuous data
Author :
Savkin, Andrey V. ; Petersen, Ian R.
Author_Institution :
Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia
Abstract :
This paper considers two related problems of state estimation and model validation for a class of uncertain linear systems. The main contribution of the paper is that it considers a general information structure which allows for discrete and continuous measurements as well as missing data. The results are given in terms of a recursive state estimator involving a jump Riccati differential equation and jump state equations. These equations can be solved online
Keywords :
Riccati equations; nonlinear differential equations; recursive estimation; state estimation; uncertain systems; continuous measurements; discrete measurements; information structure; jump Riccati differential equation; jump state equations; missing discrete-continuous data; model validation; recursive state estimator; state estimation; uncertain continuous-time systems; Differential equations; Filtering; Integral equations; Kalman filters; Linear systems; Riccati equations; Robustness; State estimation; Uncertain systems; Uncertainty;
Conference_Titel :
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-3590-2
DOI :
10.1109/CDC.1996.574381
