Design of ADRC Based on MPGA Parameters Self-tuning for Guidance System

The high-speed maglev train guidance system is an important device for the offset between the train and the track to ensure the safe driving of the train. In the process of operation, the interferences of guidance system are complex and changeable. In order to improve the tracking ability and anti-interference ability for gap change, this paper designs an Active Disturbance Rejection Controller (ADRC) for the guidance system of high-speed maglev train. To solve the problem of that parameters tuning of ADRC is complex and it is difficult to achieve good control effect by manual tuning, a parameter optimization method based on Multi Population Genetic Algorithm (MPGA) is proposed to intelligently tune the parameters of ADRC. The simulation results show that the parameters adjusted by the intelligent algorithm can make the ADRC have better control performance.