Abstract
On the basis of self-tuning regulators attention is given to theoretical and practical aspects dealing with the application of adaptive control to ship course keeping. In this paper a LQG optimal controller is developed which avoids the difficulty of solving Riccati equation on line. An extended state vector Kaiman filter is designed to improve its robustness and convergence. Parameters in both the LQG controller and Kaiman filter are estimated by recursive least square identification so that the scheme has a high degree of adaptability in the time-variant environment. The control strategies are implemented in a microcomputerized adaptive control unit which has been attached to the autopilot on board “YUHMCand undergone the sea trials. Results of experiment show that self-tuning regulators reduce the propulsion losses in addition to keeping the course satisfactorily.
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