Research On Digital Controller Of Hybrid Magnetic Bearing System

Hybrid magnetic bearings are currently widely used magnetic bearings,which have high stiffness,high precision,and no friction.This article focuses on the control algorithm of hybrid magnetic bearings and conducts research to provide theoretical and technical support for the design and control of hybrid magnetic bearings.Firstly,the structure and basic working principle of the hybrid magnetic bearing system are mainly introduced,and the magnetic circuit mathematical model and linearized equation of the system are derived using the accurate magnetic circuit method.By contrasting the simulation outcomes with the mathematical equation,the linear and nonlinear ranges of the system are determined,offering a theoretical groundwork for the subsequent investigation of control algorithms.The traditional PID controller has poor robustness and is sensitive to measurement noise and parameter disturbances,which may result in a reduction of control precision.To address this problem,an incomplete differential PID digital controller is proposed.The simulation and experimental findings demonstrate that the hybrid magnetic bearing system under incomplete differential PID control has high steady-state accuracy and strong anti-interference ability,which confirms the practicability of the proposed approach.In order to enhance the adaptability of the hybrid magnetic bearing system to modeling errors and environmental disturbances,this article suggests a method for generalized predictive control(GPC)for the hybrid magnetic bearing.The method is analyzed in terms of its control effect on the radial degree-of-freedom levitation and suppression of external disturbances.The paper also compares the effects of the main control parameters on system performance with those of traditional PID control methods.Simulation results demonstrate that the proposed GPC system has better dynamic performance and robustness.To address the issues of large parameter perturbations and weak disturbance rejection capability in hybrid magnetic bearing systems,this paper proposes an H∞ optimization control algorithm.In order to solve the difficulty of setting the weighting function and the need for operator experience and repeated attempts to achieve better control effects,the genetic algorithm-nonlinear programming(GA-NLP)method is used for global optimization of the H∞ control.The optimized H∞ control has better dynamic performance and robustness than the original H∞ control,as verified through simulation.Finally,the stability and performance of the controller were analyzed and evaluated in detail through experimental research,verifying the feasibility and effectiveness of the proposed method.