Adaptive Autopilot with Wave Filter

Abstract

This paper is concerned with analysis and design of an adaptive autopilot for ships. The design is based on a low and high frequency model of the vessel motion adequate to ship steering. The low frequency model describes the vessel response to rudder control and slowly varying environmental forces. The high frequency model represents the wave induced oscillatory part of the yaw motion. The models are used in a Kalmanfilter and the rudder control is computed from linear quadratic theory based on the low frequency part of the state vector. This yields a very effective filtering of the wave component of the yaw motion. Proper operation of this filter/controller structure requires knowledge of the vessel model parameters and the dominating wave frequency. The vessel parameters are estimated on line by a recursive prediction error method. In order to reduce the computing requirements, the state estimator is operated using scheduled gains. This results in an easy and robust design. The Convergence properties are investigated by using the method of Ljung. The performance is exemplified by simulation experiments.