Title :
Robust H2 filtering for uncertain systems with measurable inputs
Author :
de Souza, Carlos E. ; Shaked, Uri
Author_Institution :
Dept. of Syst. & Control, Lab. Nacional de Computacao Cientifica, Petropolis, Brazil
fDate :
8/1/1999 12:00:00 AM
Abstract :
This paper deals with the robust minimum variance filtering problem for linear time-varying systems subject to a measurable input and to norm bounded parameter uncertainty in the state and/or the output matrices of the state-space model. The problem addressed is the design of linear filters having an error variance with a guaranteed upper bound for any allowed uncertainty and any input of bounded energy. Three types of input signals are considered: a signal that is a priori known for the whole time interval, an unknown signal of very large bandwidth that is perfectly measured on-line, and a large bandwidth signal that is measured ahead of time in a fixed preview time interval. Both the time-varying finite-horizon and stationary infinite-horizon cases are treated
Keywords :
filtering theory; matrix algebra; noise; state-space methods; time-varying systems; uncertain systems; bounded energy input; error variance; fixed preview time interval; guaranteed upper bound; input signals; large bandwidth signal; linear filters design; linear time-varying systems; measurable inputs; measurable stochastic noise input; norm bounded parameter uncertainty; online measured signal; output matrix; robust H2 filtering; robust minimum variance filtering; state matrix; state-space model; stationary infinite-horizon; time-varying finite-horizon; uncertain systems; very large bandwidth signal; Bandwidth; Estimation error; Filtering; Measurement uncertainty; Noise measurement; Noise robustness; Nonlinear filters; Signal processing; Uncertain systems; Upper bound;
Journal_Title :
Signal Processing, IEEE Transactions on
