Research On Parameter Optimization Active Disturbance Rejection Control Based On Magnetic Levitation System

The magnetic levitation technology makes the object levitate to avoid friction with the contact surface,which has the advantages of saving energy and prolonging the service life of the equipment.However,the magnetic levitation system has the characteristics of time delay,nonlinearity and uncertainty.If the controller is designed according to the system model,when the parameters of the system are changed due to the influence of the external environment,the performance of the control system will be deteriorated.Therefore,researching a practical and reliable control system is the key to applying maglev technology to real life.Aiming at the nonlinearity of the magnetic levitation ball system and the possibility of uncertain disturbance during the suspension process of the small ball.In this paper,the active disturbance rejection control technology is used to compensate the uncertain disturbance of the magnetic levitation ball system,so as to reduce the nonlinear degree of the magnetic suspension ball system and improve the anti-disturbance performance of the system.In this regard,this paper makes the following work.Firstly,taking the working principle of the magnetic levitation ball system as the breakthrough point,the structural composition and system equation of the magnetic levitation ball system are discussed,as well as the attention points in the modeling process of the magnetic levitation ball system.The nonlinear equation of the system is linearized near the operating point,the transfer function of the system is calculated,and the stability and controllability of the system are analyzed by control theory.The performance of PID control applied in the magnetic suspension ball system is analyzed by the position stiffness and current stiffness of the magnetic suspension ball system.Then,the position closed-loop control of the magnetic levitation ball system is designed by the active disturbance rejection controller,and the signal is filtered by adjusting the speed factor and filter factor of the tracking differentiator to improve the stability of the magnetic levitation ball system.Since the extended state observer is the core component of the ADRC,its observation accuracy affects the disturbance rejection performance of the system.The error analysis of the extended state observer is carried out,and the tuning process of the parameters of the extended state observer and the control rate parameters by the frequency domain method is introduced..However,the frequency domain method is more complicated to tune.In order to improve the parameter tuning efficiency of the ADRC,an improved particle swarm algorithm is designed to optimize the parameters of the ADRC.The adaptive speed weight and the Cauchy mutation strategy are used to improve the optimization speed and accuracy of the particles.Through the optimization test of the test function,it is proved that the improved particle swarm optimization algorithm has a good convergence speed and accuracy.Finally,the improved particle swarm algorithm is used to tune the parameters of the ADRC.The optimized parameters are brought into the experimental platform of the magnetic levitation system,and the motion of the ball is observed by inputting different signals,and compared with the PID control experiment to verify the anti-disturbance performance and adaptive performance of the active disturbance rejection control magnetic levitation ball system.Experiments show that ADRC can improve system stability and self-adaptability,and can reduce system overshoot in time under the influence of external disturbance,and its control performance is superior to PID control.At the same time,the particle swarm algorithm is introduced to optimize the parameters of the ADRC,which solves the tedious problem of parameter tuning.