Title :
The robust prediction problem for a class of uncertain systems
Author :
Moheimani, S. O Reza ; Savkin, Andrey V. ; Petersen, Ian R.
Author_Institution :
Dept. of Electr. & Electron. Eng., Australian Defence Force Acad., Canberra, ACT, Australia
Abstract :
This paper is concerned with the robust prediction problem for a class of uncertain systems. In this problem, the noise and uncertainty are modelled deterministically via an integral quadratic constraint. The robust prediction problem involves constructing the set of all possible states at the current time t consistent with given output measurements up to a time τ<t and the integral quadratic constraint. This set is found to be an ellipsoid which is constructed by solving a Riccati differential equation
Keywords :
Riccati equations; constraint theory; nonlinear differential equations; prediction theory; robust control; uncertain systems; Riccati differential equation; deterministic model; ellipsoid set; integral quadratic constraint; noise; robust prediction; uncertain system; Ellipsoids; Filtering; Force sensors; Linear systems; Noise measurement; Noise robustness; Signal processing; Smoothing methods; Time measurement; Uncertain systems;
Conference_Titel :
Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3073-0
DOI :
10.1109/ISCAS.1996.541634
