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| Self-Learning Anti-Disturbance Control Strategy for High-Speed Linear Induction Motor |
| Xu Fei1,2,3, Jiang Xinyu1,2, Li Zixin1,2,3, Shi Liming1,2,3, Li Yaohua1,2,3 |
1. State Key Laboratory of High Density Electromagnetic Power and Systems Institute of Electrical Engineering Chinese Academy of Sciences Beijing 100190 China;
2. University of Chinese Academy of Sciences Beijing 100049 China;
3. Institute of Electrical Engineering and Advanced Electromagnetic Drive Technology QILU ZHONGKE Jinan 250100 China |
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Abstract High-speed linear induction motors have the advantages of light rotor mass, simple structure, and high reliability, which are suitable for ground ultra-high-speed test facilities and electromagnetic launch fields. However, when high-speed linear induction motors run at transonic speeds, the unsteady aerodynamic characteristics of shock waves will cause strong vibrations in the rotor, resulting in strong uncertain disturbances in the position and speed measurement of the linear motor rotor and the electromagnetic mechanism. This uncertain disturbance is short-term, highly dynamic, sudden, and unpredictable. Consequently, slip control of the linear induction motor is abnormal, thrust control is unstable, and the transonic operation fails, seriously restricting the system speed improvement.
This paper establishes a self-learning mathematical model of a high-speed linear induction motor. The parameters of the motor model are learned through historical experimental data to realize high-precision multi-step prediction of the mover speed. The prediction speed constructs the rolling prediction matrix, the sensor measurement speed is calculated, and a method for reliability evaluation of the measurement speed is proposed based on the variation degree of the matrix column vector. Finally, according to the weighting of the prediction velocity, the measurement data, and the credibility value, a self-learning anti-disturbance control strategy for a high-speed linear induction motor under uncertain disturbance is proposed to realize the anti-disturbance control under transonic speed conditions.
The simulation and experimental results show that the proposed model can realize linear motor rotors’ high-precision multi-step rapid speed prediction. The speed correction method blocks the propagation of uncertain disturbances and accurately suppresses uncertain disturbances. The rotor speed’s simulation error is less than 0.7%, and the experimental error is less than 1%. Under the uncertain disturbance of e=0.2, the proposed self-learning anti-disturbance control strategy can realize the stable control of dq axis current and thrust with good uncertain disturbance suppression capability. The research results can be applied to high-speed linear induction motor propulsion systems.
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Received: 14 September 2024
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2025, Vol. 40 
