A stochastic rudder control law for ship path-following autopilots

A heuristic stochastic rudder control law for ship automatic path-following in restricted waters is presented. The objective is to make feasible an automatic pilot with an adaptive capacity of operating in situations where there is a great lack of knowledge of ship dynamics. State estimation and feedback control determination are separately treated. The extended Kalman filter is combined with a dynamical model compensation technique and a state noise adjustment procedure, in a situation where the observations have a high local level of information. An adaptive scheme results where unmodeled effects are estimated together with the system state. A feedback control law that uses state estimation information and steering conditions is proposed. In each discretization interval it takes a stepwise approximation for the control, as the solution of a parameter estimation problem. The performance of the resulting state estimator and controller is illustrated by results obtained through digital simulation. The test case selected is that of ship automatically steering in a channel under severe geometric and environmental conditions.

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