Rotor Resistance Online Identification of Vector Controlled Induction Motor Based on Neural Network. (25th September 2014)

• Record Type: Journal Article
• Authors: Fan, Bo; Yang, Zhixin; Xu, Wei; Wang, Xianbo
• Other Names: Zhang Chengjin Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2014(2014)
• Publication Date: 2014-09-25
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2014/831839
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Rotor resistance identification has been well recognized as one of the most critical factors affecting the theoretical study and applications of AC motor's control for high performance variable frequency speed adjustment. This paper proposes a novel model for rotor resistance parameters identification based on Elman neural networks. Elman recurrent neural network is capable of performing nonlinear function approximation and possesses the ability of time-variable characteristic adaptation. Those influencing factors of specified parameter are analyzed, respectively, and various work states are covered to ensure the completeness of the training samples. Through signal preprocessing on samples and training dataset, different input parameters identifications with one network are compared and analyzed. The trained Elman neural network, applied in the identification model, is able to efficiently predict the rotor resistance in high accuracy. The simulation and experimental results show that the proposed method owns extensive adaptability and performs very well in its application to vector controlled induction motor. This identification method is able to enhance the performance of induction motor's variable-frequency speed regulation.