Intelligent autonomous control for ocean surface vehicle

This paper is concerned with the Intelligent Autonomous Control (IAC) techniques for improving the performance of ocean surface vehicle integrated control. An autonomous intelligent control algorithm for surface ship autopilot and main propulsion engine integrated control is proposed. A general fuzzified cerebellar model articulation controller with eligibility (FCE), which possesses good real-time learning characteristics, is discussed and applied to ocean surface vehicle intelligent control. The simulation results show that the ship course can be properly controlled in cases where additional sea state disturbances of wave, wind, current are present. It is demonstrated that the proposed algorithm is a promising alternative to conventional autopilots. Intelligent autonomous control system is great significant to improve ocean surface vehicle performance of control and also helpful to extend the using time of main engine.