A design of optimal receding horizon filter for linear systems with uncertainty

An optimal receding horizon filter robust against temporary modeling errors is proposed. Unlike previous works, a proposed filter is a low-complexity, easy to implement. Also, it gives us the optimal solution which is the same as the optimal FIR filter and recursive FIR forms designed by Kwon et al. [2]. A new optimal receding horizon filter is composed largely of two sets of equations. The sets of Lyapunov equations and the celebrated Kalman equations fully describe the proposed filter. The content of this paper includes the discrete and continuous versions of linear systems. Finally, the performance of the proposed filter is tested through numerical examples.