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| Resonant Frequency Tracking Control of Linear Oscillatory Machine Based on Integral Sliding Mode Observer |
| Liao Kaiju1, Xu Wei2,3, Ge Jian3, Li Dongyi3, Su Shihu4, Deng Jiangming5 |
1. Key Laboratory of High Density Electromagnetic Power and Systems (Chinese Academy of Sciences) Institute of Electrical Engineering Chinese Academy of Sciences Beijing 100190 China;
2. Research Institute of Huazhong University of Science and Technology in Shenzhen Shenzhen 518052 China;
3. State Key Laboratory of Advanced Electromagnetic Technology Huazhong University of Science and Technology Wuhan 430074 China;
4. CRRC Zhuzhou Motor Co. Ltd Zhuzhou 412001 China;
5. CRRC Zhuzhou Locomotive Co. Ltd Zhuzhou 412001 China |
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Abstract In order to improve the safety and reliability of the system and achieve maximum output efficiency, it is necessary to simultaneously implement position sensorless piston stroke closed-loop control and resonant frequency tracking control for the linear oscillatory machine (LOM). Existing control methods for position sensorless resonance frequency tracking have low stroke estimation accuracy and poor anti-interference ability, which causes low resonant frequency tracking accuracy and severe frequency oscillation. This paper investigates a new resonant frequency tracking control method based on the integrated sliding mode observer (ISMO).
When the LOM operates at the system resonant frequency point, the phase difference between stroke and current is exactly 90°. Accordingly, a double cross-correlation function ratio (DCFR) method is proposed to track the system resonant frequency. A second-order generalized integrator (SOGI) generates the current orthogonal signal. This method can eliminate the influence of stroke on resonance frequency tracking control, thereby improving the anti-interference ability of the control system. An integrated sliding mode surface and a new reaching law are used to design an ISMO to reconstruct the information of back electromotive force (EMF). Since the back EMF is positively proportional to the velocity signal, the piston velocity can be calculated. The piston stroke can be obtained by integrating the velocity signal. However, specific DC components exist in the measured voltage and current, and a pure integrator can cause the integral saturation problem. Therefore, an SOGI is used to filter the estimated back EMF signal to obtain the accurate stroke estimation signal. Finally, due to the strong parameter robustness of ISMO and the anti-interference ability of DCFR, the combination of ISMO and DCFR is used to achieve the position sensorless resonant frequency tracking control. Experimental results show that the proposed method effectively improves the tracking accuracy, settling time, and anti-interference ability.
The following conclusions can be drawn from the experiment analysis. (1) The constructed ISMO has higher stroke estimation accuracy than the back electromotive force integration method. (2) The position sensorless resonant frequency tracking control can be achieved using the estimated stroke signals of ISMO. (3) By constructing the ratio of two DC components, the proposed DCFR method eliminates the influence of stroke variation and obtains steady and accurate resonant frequency tracking results. (4) Based on the DCFR method, the ISMO and back EMF integration methods are used to track the resonant frequency. The results show that ISMO achieves higher tracking accuracy by providing more accurate stroke signals than the conventional back EMF.
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Received: 29 May 2023
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2024, Vol. 39 
