摘要： 标准粒子群优化算法的速度更新机制为比例-积分(PI)控制策略,而由于其中固有积分项的存在,系统容易产生振荡,导致搜索速度慢。为此,根据比例-积分-微分(PID)控制特性,提出一种快速粒子群优化算法。在标准粒子群及其改进算法中加入微分控制来克服振荡,提高收敛速度,增加搜索过程的稳定性。仿真结果表明,与标准粒子群算法和全信息粒子群算法相比,该算法在保证寻优精度和可靠性的同时,大幅提高了寻优速度,具有较高的运算效率。

关键词: 粒子群优化, 控制策略, 微分控制, 偏差, 收敛速度

Abstract: The velocity updating mechanism of Particle Swarm Optimization(PSO) algorithm is Proportion-Integral(PI) control strategy.On account of the inherent integral term,the system is prone to oscillation,which leads to the low search speed.Therefore,according to the characteristics of Proportional-Integral-Derivative(PID) control,this paper proposes a fast PSO algorithm.The differential control is added in the standard PSO algorithm and its improved algorithm to overcome the oscillation,improve the convergence speed,and increase the stability of the search process in the meantime.Simulation results show that,compared with the standard PSO algorithm and the full information PSO algorithm,the proposed algorithm improves the search speed and has high computing efficiency while ensuring the optimization accuracy and reliability.

Key words: Particle Swarm Optimization(PSO), control strategy, differential control, deviation, convergence speed

中图分类号: 

• TP301.6