Research on drive control method of induction motor based on random forest

• Published in: 2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) pp. 444 - 450
• Main Authors: Shao, Wen-Mian, Liu, Xian-Zhong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 25.12.2020
• Subjects: Conferences; control effect; control system synthesis; control wave amplitude; drive control; drive control instability; fuzzy control; fuzzy rules; fuzzy set theory; Hardware; high temperature; high temperature environments; induction motor; induction motor drive control method; induction motor drive controller; induction motor drives; low temperature; low temperature environments; machine control; random forest; random forest algorithm; random forest theory; Random forests; Temperature; temperature control; Thermal stability; working characteristics
• DOI: 10.1109/IAAI51705.2020.9332861

The induction motor is one of the key hardware for the normal operation of mechanical equipment. However, due to the poor performance of the controller designed by the traditional method, it is easy to cause the drive control instability. Therefore, the induction motor drive control method based on random forest is studied. This method obtains in advance the working characteristics of induction motors in high and low temperature environments; considering the working characteristics, a new induction motor drive controller is designed based on the random forest algorithm; and the induction motor drive control is realized by setting fuzzy rules. The experimental results show that in the high temperature and low temperature test environment, the drive control method studied in this study has regularity in the control wave amplitude and the control effect is more stable. It can be seen that the random forest theory meets the requirements of this research.