Fractional Order Internal Model Control of PMSM Speed Servo System

Authors

Zhicheng Zhao, School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;
Sang Hai, School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;
Jinggang Zhang, School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;

Abstract

Abstract: A design method of fractional order (FO) internal model controller for permanent magnet synchronous motor (PMSM) speed servo system was proposed. The simplified mathematical model of speed servo system was built. Based on internal model control (IMC) principle, the FO internal model controller was deduced by using the FO filter to replace the integer order one. The proposed controller contained only two adjustable parameters, and the defects of the fractional PI^λD^μ controller tuning method were effectively overcome. Moreover, the dominant pole was selected according to the time domain performance indicators of the system, and an analytical tuning approach of the controller was given. So the blindness of selecting the controller parameter was avoided. The simulation results show that the proposed method not only could provide a better dynamic performance of both the command tracking and disturbance rejection for PMSM speed servo system, but also provide a better robustness against parameters perturbation.

Recommended Citation

Zhao, Zhicheng; Hai, Sang; and Zhang, Jinggang (2020) "Fractional Order Internal Model Control of PMSM Speed Servo System," Journal of System Simulation: Vol. 27: Iss. 2, Article 22.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss2/22

First Page

384

Revised Date

2014-04-28

DOI Link

https://doi.org/

Last Page

388

CLC

TP273

Recommended Citation

Zhao Zhicheng, Sang Hai, Zhang Jinggang. Fractional Order Internal Model Control of PMSM Speed Servo System[J]. Journal of System Simulation, 2015, 27(2): 384-388.