The proposal is to put on top of a conventional slew motor in a piggyback fashion a tracking motor that can develop high torques over a limited range. Such a system will satisfy the required high tracking performance but it presents a new control action problem. A solution to the problem is proposed involving a microprocessor-based monitor to realign the slow motor occasionally. When the tracking system is designed to operate on board ship, then two signals need consideration: The absolute target motion in space and the disturbance from ship rolling. The monitor is mainly to model these motions. The target motion and ship rolling are modelled with a quadratic polynomial and an autoregressive model, respectively. The parameters of the models are estimated in real-time using a Finite Memory Kalman Filter, The theory of the filter is that the parameters are estimated based on a finite number of past measurements such that the expected estimation error squares is minimum. Anticipated target motion and ship rolling can be predicted using the estimated models. An optimal control strategy using the estimated models is then calculated. The control action is optimal in the sense that the probability of target loss weighted with the frequency of realigning the slew motor is minimal. The tracking motor responds directly to the target motion and disturbance. However, certain parameters of the tracking motor could be up-dated by the monitor to improve tracking performance.