微型电脑应用2025，Vol.41Issue(3)：234-238,5.
基于多目标遗传算法的伺服控制参数整定研究
Research on Servo Control Parameter Tuning Based on Multi-objective Genetic Algorithm
张进年1
作者信息
- 1. 铜川职业技术学院,机电工程学院,陕西,铜川 727031
- 折叠
摘要
Abstract
Proportional-integral-differential(PID)controllers are commonly used in servo-based linear motion systems to correct positioning errors due to thermal expansion of the ball screw assembly and encoder measurements.Different conventional and heuristic methods are available for optimal PID tuning of servo controllers in linear motion systems.However,the existing er-ror minimization functions based on integral or performance metrics cannot meet all the performance requirements of dynamic systems.To address this problem,this paper establishes a multi-objective cost function containing the absolute error function of the integration time and the parameters of the performance indexes such as rise time,regulation time and overshoot,based on the Pareto solution obtained by the multi-objective genetic algorithm(MOGA).The proposed objective function is used to rectify the PID controller model of linear motion system by using particle swarm optimization algorithm and aquila optimization algorithm.The algorithm was validated in Lab VIEW environment and the experimental results proved the effectiveness of the algorithm.关键词
比例-积分-微分控制器/伺服电机/多目标遗传算法/粒子群优化/天鹰优化Key words
PID controller/servo motor/multi-objective genetic algorithm/particle swarm optimization/aquila optimization分类
计算机与自动化引用本文复制引用
张进年..基于多目标遗传算法的伺服控制参数整定研究[J].微型电脑应用,2025,41(3):234-238,5.
