改进型粒子群算法磁致伸缩作动器的跟踪控制

Position Tracking Control of Magnetostrictive Actuator Using Improved PSO Algorithm

在低频条件下,以磁致伸缩作动器线性模型为基础,设计了PID及前馈PID控制器。针对固定参数控制器自适应能力较弱的现状,提出用粒子群(PSO)算法对固定参数控制器进行优化。针对标准PSO算法存在早熟收敛、后期迭代易陷入局部最优的不足,进一步提出了一种可动态调整惯性权重及遗传变异的改进型粒子群(IPSO)优化算法,并将该算法与前馈PID相结合应用于磁致伸缩作动器的位置跟踪控制。仿真结果表明:针对指令阶跃信号,相对传统PID及前馈PID控制,改进型PSO前馈PID控制具有控制精度高,位置跟踪效果好及抗干扰能力强的特点。

Based on the linear model of magnetostrictive actuator, the PID and feedforward PID controllers were designed in low frequencies.For the situation that the adaptive capacity of fixed parameter controller is weak, then the particle swarm optimi-zation （ PSO） algorithm was proposed to optimize the fixed controller parameter.The standard PSO algorithm is insufficient with premature convergence and easily falling into local optimum in later iteration.An improved particle swarm optimization （ IPSO） was further proposed with a dynamic change of inertia weights and genetic variation.Then it was applied to the position tracking control of magnetostrictive actuator with the combination of feedforward PID.And then simulation results show that：for the step signal instruction, compared with traditional PID and feedforward PID control, the improved PSO feedforward PID control has the characteristics of higher control accuracy, better location tracking performance and stronger anti-interference ability.