*Article* **Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives**

**Yang Liu \*, Jin Zhao and Quan Yin**

School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China; jinzhao617@hust.edu.cn (J.Z.); yinquans@hust.edu.cn (Q.Y.) **\*** Correspondence: yangliu30@hust.edu.cn; Tel.: +86-138-7110-9968

**Abstract:** In this paper, a model-based predictive rotor field-oriented angle compensation approach is proposed for induction machine drives. Indirect rotor field-oriented control is widely used in induction machine drives for its simple implementation and low cost. However, the accuracy of the rotor field-oriented angle is affected by variable parameters such as the rotor resistance and inductance. An inaccurate rotor field-oriented angle leads to a degradation of the torque and dynamic performance, especially in the high-speed flux-weakening region. Therefore, the d-axis and q-axis currents in the rotation reference frame are predicted based on the model and compared with the feedback current to correct the rotor field-oriented angle. To improve the stability and robustness, the proposed predictive algorithm is based on the storage current, voltage, and velocity data. The algorithm can be easily realized in real-time. Finally, the simulated and experimental results verify the algorithm's effectiveness on a 7.5 kW induction machine setup.

**Keywords:** rotor field-oriented angle error; indirect rotor field-oriented control; induction machine drives; model-based prediction
