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Generalized predictive voltage control strategy for independent excitation DC power generation system
Xia Yuhang, Wang Yu, Chen Kai, Zhang Chenggao
School of Automation Nanjing University of Aeronautics and Astronautics Nanjing 211100 China

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Abstract  

The voltage closed-loop control based on the PI regulator is generally adopted in the independent excitation DC power generation system. PI control can ensure the steady-state control accuracy of the system output voltage. However, limited by the fixed PI regulator parameters and the nonlinearity of the system itself, the dynamic regulation characteristics of the output voltage may have problems such as slow response speed and extensive voltage recovery overshooting when the system faces load mutation under different working conditions. In recent years, predictive control has been widely used in power electronics with its characteristics of fast dynamic response and strong resistance to disturbance. Among them, the generalized predictive control (GPC) based on multi-step prediction has the characteristics of high flexibility in parameter design and strong robustness when the prediction length is sufficient. As an alternative to PI control, it can improve the voltage dynamic performance of the system under load disturbance.
It is a standard solution to introduce load current feedforward to solve the problem of the poor dynamic performance of PI control. Considering that the relation curve between excitation and load of the power generation system is coupled with the parameter of generator speed, the fitting function relation surface of excitation, load, and speed is constructed. After adding the feedback value of load current to the total generalized predicted output, the excitation current command value is obtained through the fitting function.
The control loop of the system is approximately linearized by the fitting function, and the transfer function in the discrete domain of the control system is constructed to analyze the system's stability and ability to resist load disturbance. The system stability is judged by the closed-loop pole position in the discrete domain. When the weight coefficient r of the performance index function is small, the system is unstable. When the predicted length N, the weight factor RF, and the estimated capacitance value C of the load end change within a specific range, the closed-loop pole trajectory of the control system always lies in the unit circle, and the system is stable. The control parameters used in the final experiment are determined by analyzing anti-load disturbance ability. The smaller r value and more considerable N value can give the system more excellent anti-disturbance ability. However, Considering the limited computing power of the MCU in the interrupt cycle, the N value can not be too large in the experiment.
Comparing the proposed GPC method with the PI method, the steady-state experiment, load disturbance dynamic experiment, and control algorithm complexity experiment are carried out, respectively. Finally, according to the experimental results, the following conclusions are drawn: 1) The GPC method based on the fitting function relationship can realize the closed-loop voltage control of the system and still has enough control accuracy when the speed changes. 2) Compared with the PI control method, the DC power generation system under the control of GPC has a significantly improved dynamic performance in the face of different load mutations. 3) When the prediction length of GPC is considerable, compared with simple PI control, the MCU space and computing time required by the GPC algorithm are larger.
Key words： Independent excitation DC generator system      Generalized predictive control      load disturbance      dynamic performance     
PACS: TM301  
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Xia Yuhang
Wang Yu
Chen Kai
Zhang Chenggao
Cite this article:   
Xia Yuhang,Wang Yu,Chen Kai等. Generalized predictive voltage control strategy for independent excitation DC power generation system[J]. Transactions of China Electrotechnical Society, 0, (): 12-12.
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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.220673     OR     https://dgjsxb.ces-transaction.com/EN/Y0/V/I/12
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