volume | PIER Journals

Abstract

To enhance the reaction speed, suspension performance, and anti-interference ability of a Bearingless Induction Motor (BIM) operation control system, an improved Active Disturbance Rejection Control (ADRC) technique is proposed. Firstly, the ADRC in the suspension system and the ADRC in the torque system are designed, respectively, using the BIM's mathematical model as the basis. Furthermore, the error integral signal is incorporated into the nonlinear state error feedback control law of the standard ADRC controller. Subsequently, a novel optimal control function is formulated using the fitting method, which is based on the original fal function. This approach effectively mitigates the impact of output signal fluctuations at the inflection point of the fal function. Simultaneously, the RBF neural network technique is employed to autonomously adjust the control parameters of the extended state observer, therefore enhancing the system's observation capability. Ultimately, the classic ADRC control strategy and the IADRC strategy are compared through simulation and experimentation. Simulations and experimental findings demonstrate that the suggested control method enhances the BIM control system's response time and resilience to external disturbance. Additionally, it enhances the levitation performance of the BIM system.

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Mr. Xiang Wang

Professor Zebin Yang

Professor Xiaodong Sun

Dr. Shihan Zhan