Robust H/sub 2/ filtering for uncertain systems with measurable inputs

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.