Model predictive control of brushless doubly fed twin stator induction machine: A model reduction approach

Publication Type:
Conference Proceeding
Citation:
2017 20th International Conference on Electrical Machines and Systems, ICEMS 2017, 2017
Issue Date:
2017-10-02
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© 2017 IEEE. This, paper presents a model predictive control (MPC) scheme and its model reduction approach for the brushless doubly fed twin stator induction machine (BDFTSIM). Firstly, the state-space equations of BDFTSIM, in terms of (power winding) PW flux, (rotor winding) RW flux, and (control winding) CW flux, is derived for developing the complete power model which is explicitly used to predict the future behavior. However, the MPC based on the complete model is too complicated for real time application. Therefore, a relevant model reduction approach is then developed for simplifying the power model while maintaining the accuracy under various conditions. Finally, by comparing the simulation results of the MPC based on the reduced model and complete model respectively, the effectiveness of the proposed method is verified.
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