Nonlinear cloud model control for ship steering based on genetic algorithms

A cloud model controller for ship steering is developed with nonlinear behavior and uncertain problems of ship motion. The fast Elitist non-dominating sorting genetic algorithm II (NSGA-II) is employed to optimize the parameters of the controller. Analysis and simulation results show the design of the cloud model controller based on multi-objective optimization of genetic algorithm is effective and the controller has good control performance and strong robustness.