Optimal worst case estimation for LPV-FIR models with bounded errors

In this paper discrete time linear parameter varying (LPV) models with finite impulse response (FIR) dynamic structure are considered. Measurement errors are assumed to be bounded and in such condition the worst case parameter estimate errors are derived together with the input sequences that allow their determination. The main result of the paper shows that the optimal input design of LPV-FIR models is achieved by combining the available results on optimal input design for invariant FIR models with the results on optimal input design for static blocks.