MINIMAX L{sub}2-E{sub}2 FIR FILTERS FOR DETERMINISTIC CONTINUOUS-TIME STATE SPACE SIGNAL MODELS

摘要

In this paper, a new minimax L{sub}2-E{sub}2 performance criterion is introduced, which is represented as a worst case gain between the disturbance during the recent time interval and the current estimation error. Minimax L{sub}2-E{sub}2 FIR filter (MLEFF) is proposed for deterministic continuous-time state space signal models. The MLEFF is designed to minimize the maximum value of the L{sub}2-E{sub}2 performance criterion-together with linearity, unbiased property in the deterministic sense, FIR, structure, and independence of the initial state information, simultaneously. The MLEPF is shown to be robust with respect to model uncertainties due to FIR, structure and disturbances due to the worst case design. For efficient implementation, it is shown that the MLEFF can be expressed recursively. It is also shown to be optimal for the performance criterion for each component of the state.