Title :
Improved model predictive control of permanent magnet synchronous motor
Author :
Xuan Wu ; Hui Wang ; Shoudao Huang ; Yaojing Feng
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);
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2014 17th International Conference on
Conference_Location :
Hangzhou
DOI :
10.1109/ICEMS.2014.7013540
