MODEL ERROR COMPENSATION FOR OBSERVER DESIGN

We consider the state and disturbance estimation problem for a linear system with uncertainties as additive deterministic disturbances. Inst ead of attempting to minimize the effects of the disturbance as in the robust filters or to decouple the disturbance as in the unknown input observers, it is proposed to estimate the disturbance and to use it t o reduce the model error and thus to improve the state estimation. Thi s technique is denoted as model error compensator (MEG). Sufficient co nditions for achieving bounded disturbance estimation error are presen ted. These conditions are different from those required in the unknown input observers and the robust filter for state estimation only. In a ddition, no differentiation of the measured signals is required. This paper also discusses how existing state observers can be used with the MEC as a two-step observer design strategy.