Analysis of PID control for magnetic suspension based on improved particle swarm optimization algorithm
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.
magnetic suspensionparticle swarm optimization algorithmPID controlparameter optimization
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