Abstract
The performance robustness of a prediction-type Kalman filter is considered for linear discrete-time systems with structured plant uncertainty and noise uncertainty. Two methods are proposed to achieve upper and lower bounds on the mean square of the estimation error, measuring the effect of the uncertainty on the performance of the filter. An illustrative example is given