Application of the genetic particle swarm optimization algorithm in dynamic positioning ship control

Aiming at the issue of precise fixed point control of the vessel dynamic positioning system and combining the unique function of the genetic algorithm such as sound selection of cross mutant objects and good memory for the characters of the particle swarm algorithm, a genetic particle swarm optimization algorithm is proposed in this paper and applied to the weight coefficient selection of the performance index weighting matrix of the optimal control. Through a marine multipurpose ship dynamic positioning point control simulation, the position of surge and sway as well as the angle of yaw gradually reach the desired value, and all output values are seen to converge and bounded. Compared with the results obtained in the traditional optimal control, the proposed algorithm is more effective and yields better optimization performance of the genetic particle swarm in the optimal control, and is thus more suitable for marine engineering applications.