基于粒子群优化算法的水下航行器深度控制研究

Research on Depth Control of Underwater Vehicle Based on Particle Swarm Optimization (PSO) Algorithm

提出了一种基于粒子群优化算法的水下航行器深度控制器参数优化设计方法。针对水下航行器运动参数变化的特性,采用粒子群优化算法收敛速度快、寻优特性好等特点,将其应用到控制器参数的优化设计中。仿真结果表明,利用粒子群优化算法进行优化设计的水下航行器深度控制器具有良好的控制性能。

A particle swarm optimization-based underwater vehicle depth controller parameter optimization method is presented in this paper.For underwater vehicle motion parameters changes,particle swarm optimization algorithm with fast convergence and optimization characteristics of good features,will be applied to optimize the design parameters of the controller.The simulation results show that the underwater vehicle depth controller optimized by the particle swarm optimization algorithm has perfect performance.