Optimal control of linear systems with time-delay and observation noise

Abstract

The problem of controlling a linear system to minimize a quadratic cost criterion is investigated when the system output is a delayed linear combination of system states corrupted by additive observation noise. It is shown that the optimal control is generated by the cascade combination of a Kalman filter and a least mean-squared predictor. Expressions are derived for the minimum cost and for the state variances.