Adaptive fuzzy control of ship autopilots with uncertain nonlinear systems

This paper presents a novel adaptive fuzzy control for ship autopilots with uncertain system and gain nonlinear functions, which are all the unstructured (or non-repeatable) state-dependent unknown nonlinear functions. The Takagi-Sugeno type fuzzy logic systems are used to approximate uncertain functions and the algorithm is proposed by use of the idea of changing supply functions. The closed-loop system is proven to be semi-global asymptotical stability. In addition, the possible controller singularity problem in some of the existing adaptive control schemes met with feedback linearization techniques can be removed and the adaptive mechanism with only one learning parameterization can be achieved. The proposed methodology, which is applied to design ship autopilot to maintain the ship on a pre-determined heading, is verified using the simulation mode of Dalian Maritime University's ocean-going training ship, Yulong. Simulation results show the effectiveness of the control scheme.