基于改进粒子群算法的磁力吊PID控制分析

Analysis of PID control for magnetic suspension based on improved particle swarm optimization algorithm

该研究旨在提升磁力吊在吸附和吊运钢板过程中的控制精度与稳定性。首先根据拉格朗日方程建立磁力吊吸附钢板后的二阶微分动力学模型,并通过拉氏变换后在Simulink中建立PID控制仿真模型。为了优化PID控制器的3个控制参数,研究采用改进的粒子群算法(PSO)。具体而言,通过选取位置的积分时间绝对误差(ITAE)和均方误差(MSE)加权评价指标作为适应度函数,求解出最佳PID控制参数组合。仿真结果表明,优化后的PID控制策略在减少系统误差和控制摆幅方面表现出显著优势,同时提高了系统的响应速度和稳定性,为进一步研究和工程应用提供了参考依据。

This study aims to improve the control accuracy and stability of magnetic suspension during the adsorption and lifting of steel plates.Firstly,a second-order differential dynamic model of the magnetic suspension absorbing steel plates is established based on the Lagrange equation,and a PID control simulation model is established in Simulink after Laplace transformation.In order to optimize the three control parameters of the PID controller,this study adopts an improved particle swarm optimization algorithm(PSO).Specifically,by selecting the weighted evaluation indicators of the integration time absolute error(ITAE)and mean square error(MSE)of the position as fitness functions,the optimal combination of control parameters is solved.The simulation results show that the optimized PID control strategy exhibits significant advantages in reducing system errors and controlling swing,while improving the response speed and stability of the system,providing a reference basis for further research and engineering applications.