Uniform Demagnetization Diagnosis for Permanent-Magnet Synchronous Linear Motor Using a Sliding-Mode Velocity Controller and an ALN-MRAS Flux Observer
Jiwen Zhao, Lijun Wang, Liang Xu, Fei Dong, Juncai Song, Xing Yang
Abstract
To realize the demagnetization fault diagnosis and degree estimation of permanent-magnet synchronous linear motors in linear motion applications with high precision and multiple working conditions, a novel double closed-loop control with an adaptive linear neuron (ALN) model reference adaptive system (MRAS) flux linkage observer is proposed in this article. First, a sliding-mode control (SMC) is introduced to design the velocity loop to obtain good speed adaptability. Then, the MRAS flux observer is established, and the ALN algorithm for modifying the MRAS adaptive law online is designed combining with MRAS flux observer. In addition, the finite element models of normal, weak (F1), mild (F2), moderate (F3), and severe (F4) demagnetization faults are established, and the accurate values of flux linkage under different demagnetization degrees are simulated. Furthermore, the demagnetization fault diagnosis algorithm is introduced with an SMC-ALN-MRAS flux observer. Finally, a prototype motor experimental platform is built, and comparative experiments are designed to confirm the correctness and effectiveness of the proposed method.