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| An Optimized Model Predictive Control Method for the Induction Motor Drives Fed by an Indirect Matrix Converter |
| Mei Yang, Wang Liang, Huang Weichao |
| Inverter Technology Engineering Research Center of Beijing North China University of Technology University Beijing 100144 China |
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Abstract In the model predictive control (MPC) method for the indirect matrix converter (IMC), due to the limited switching states and the fixed control frequency, the output voltage of converter in a sampling period is limited. Under the middle and low speed conditions, the difference between each finite output voltage vector and the reference value is large, resulting in rich harmonics in the input/output currents, which in turn causes the ripple of torque and flux. In order to solve this problem, an optimized model predictive control method is proposed for the induction motor drives fed by an indirect matrix converter. In this method, the grid current and the motor flux vector are considered as the control objectives. A switching state corresponding to zero voltage vector of the inverter circuit is inserted in each sampling period, and the corresponding switching state and the optimal duty cycle are obtained by using the monotonicity of the cost function with the time constraint of the switching state. As a result, the input and output performance of the indirect matrix converter is improved. In addition, the zero-current commutation for bi-directional switches can be realized. The simulation and experimental results show that the proposed method achieves good grid power quality and dynamic/steady state performances for the induction motor. Compared with the conventional MPC, the harmonics of the input and output currents of IMC have been reduced, especially under the middle and low speed conditions.
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Received: 01 July 2018
Published: 29 July 2019
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2019, Vol. 34 
