In order to optimize the current-control performance of the permanent-magnet synchronous motor system(PMSM) with different disturbances and nonlinearity, a improved current control algorithm for the PMSM systems using Recursive Model Model Predictive Control (RMPC) is developed in this paper. Because of the conventional MPC has to be computed online, and its iterative computational procedure need long calculated time. To enhanced computational speed, a recursive method based on Recursive Levenberg Marquardt Algorithm (RLMA) and Iterative Learning Control (ILC) is introduced to solve the optimization issue in MPC. Fianl, the effectiveness of the proposed algorithms have been verified by Simulation and TMS320F28335DSP experimental results


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    Title :

    Research on the Recursive Model Predictive Control Algorithm of PMSM


    Contributors:
    Wu, Xuan (author) / Wang, Hui (author) / Huang, Sheng (author) / Huang, Shoudao (author)


    Publication date :

    2014-08-01


    Size :

    767782 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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