Optimal Moving Average Filter with Application to Self-Tuning Control against Deterministic Disturbances

The optimal moving average filter for the linear stochastic controlled plant is developed from the viewpoint of the internal model of the deterministic disturbance. filter enables the minimum-variance self-tuning control not only to effectively overcome various kinds of deterministic disturbances modelled by linear homogeneous difference equation, such as stepwise and sinusoidal disturbances, but also to greatly depress the amplification of the random noise in the control system. Thus,both the precisions of identification and the quality of control can be improved (especially in the cases of strong colored noises).