A Multi-Center PSO Algorithm with Memory Ability and Its Application to the Online Modelling of an Underwater Vehicle Thruster

Abstract

To improve the performance of Particle swarm optimization (PSO) in online optimization problems, a multi-center PSO algorithm with memory ability was proposed. Main strategies of the proposed algorithm include the initial population optimization based on historical optimal solution and improved chaos mapping and the multi-center collaborative search. To verify online optimization performance, the proposed algorithm is applied to the online modelling process of an underwater vehicle thruster to optimize the modeling parameters. Result proves the superiority of the proposed algorithm in online optimization problem. Keywords Online optimization • PSO • Tent mapping • Multi-center collaborative search • Online modeling • Underwater vehicles