Improved model predictive control of permanent magnet synchronous motor

Author

Xuan Wu ; Hui Wang ; Shoudao Huang ; Yaojing Feng

fYear

2014

fDate

22-25 Oct. 2014

Firstpage

598

Lastpage

604

Abstract

This paper depicts realization of a rapid current control system of permanent magnet synchronous motor (PMSM) based on Recursive model predictive control (RMPC). In traditional MPC can only be adopted in slow dynamics, its sample time is measured in seconds or minutes. It has to be calculated online, and its iterative computational program requires long computational time. To shorten computational time, a recursive method based on Recursive Levenberg Marquardt Algorithm (RLMA) and Iterative Learning Control (ILC) is proposed to resolve the optimization problem in MPC. Then, Simulation and TMS320F2-8335DSP experimental results show the effectiveness of RMPC compared with traditional MPC.

Keywords

electric current control; iterative methods; optimisation; permanent magnet motors; predictive control; recursive estimation; synchronous motors; ILC; PMSM; RLMA; RMPC; TMS320F2-8335DSP; current control system; iterative computational program; iterative learning control; optimization problem; permanent magnet synchronous motor; recursive Levenberg Marquardt algorithm; recursive method; recursive model predictive control; Control systems; Heuristic algorithms; Mathematical model; Optimization; Prediction algorithms; Predictive control; Predictive models; Iterative Learning Control (ILC); Permanent Magnet Synchronous Motor((PMSM); Recursive Levenberg Marquardt Algorithm(RLMA); Recursive Model Predictive Control (RMPC);

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Machines and Systems (ICEMS), 2014 17th International Conference on

Conference_Location

Hangzhou

Type

conf

DOI

10.1109/ICEMS.2014.7013540

Filename

7013540