Parameter Identification of Ship Lateral Motions Using Evolution Particle Swarm Optimization

Abstract

An evolution particle swarm optimization(EPSO) algorithm is proposed to solve the problem that particle swarm optimization(PSO) is easily trapped in the local minima. The EPSO is applied in the parameter identification of ship lateral motions. In order to increase the diversity of particle, a new evolutionary strategy in the standard PSO algorithm is introduced. Firstly, in the iterations of algorithm optimization process, EPSO algorithm is constructed to improve the capacity of global search algorithms by controlling groups of particles in the selection, variation, such as evolutionary operation and reinitializing the search boundary. Secondly, the problems of ship lateral motion parameters identification are converted to nonlinear optimization problems in continual space, and then the EPSO algorithm is used to search the parameter concurrently and efficiently to find the optimal estimation of the system parameters. The experiment results show that the ESPO algorithm can quickly identify the ship lateral motion parameters satisfying the accuracy requirement and verify the effectiveness of the proposed algorithm.