Intelligent ship autopilot system control based on generalized fuzzy hyperbolic model

In this paper, an adaptive fuzzy control algorithm is proposed for the intelligent ship autopilot system that takes into account input saturation, external disturbance, and nonlinear terms generated by strong uncertainty. Since the generalized fuzzy hyperbolic model (GFHM), the parameters of the traditional fuzzy method can be simplified, the complexity of the model can be greatly reduced, and the nonlinear function can be approximated with arbitrary precision. The algorithm proposed in this paper uses the auxiliary system to compensate the limited input signal, and the GFHM approximates the nonlinear function. The bound of all variables in the closed-loop system can be verified by the Lyapunov method. The simulation proves that the autopilot control rudder angle duration curve and the desired heading tracking error curve tend to be stable when considering the limited rudder angle input and unknown nonlinear terms. The simulation results further verify that the fuzzy algorithm in this paper can effectively control the ship's course.