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The weighting factor adjustment limits the extensive application of conventional model predictive torque control in practice. In this paper, a model predictive torque control strategy with gravitational search algorithm (GSA) is proposed. The detail of an adaptive torque variable is introduced to control the flux linkage of the induction motor, and a modified value function is constructed by using electromagnetic torque and image torque. The proposed model uses two control variables to replace the torque and flux variables in the conventional model predictive torque control and improve the control efficiency. The simulation and experimental results show that the proposed method achieves a fast dynamic performance compared to the conventional model and reduces the average switching frequency. Besides, the system has high response speed, high accuracy, stability, and a certain application value.

Improve Performance of Induction Motor Drive using Weighting Factor approach-based Gravitational Search Algorithm