Transactions of China Electrotechnical Society  2018, Vol. 33 Issue (20): 4834-4844    DOI: 10.19595/j.cnki.1000-6753.tces.171018
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Improved Model Predictive Control Based on Switching State Function Calculation
Yang Xingwu, Niu Mengjiao, Li Hao, Fu Yang
Engineering Research Center of Green Energy Grid-Connected Shanghai University of Electric Power Shanghai 200090 China

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Abstract  The traditional finite state model predictive control (FCS-MPC) uses the enumeration method to select the optimal voltage vector, resulting in a large amount of calculation of the digital controller. Therefore, a simplified MPC strategy is proposed to reduce the computational complexity while maintaining the dynamic and steady-state performance of the original algorithm. However, these methods have the disadvantages of high sampling frequency and large steady-state power errors. With the discrete prediction model of the three-phase AC-DC converter, a model predictive control method based on switching state function calculation directly is proposed in this paper, which takes negative conjugate of complex power in synchronous frame as the control variable. According to the length and the sector of the power control error vector, the switching state function of each phase is calculated directly. The precise tracking control of system power is also carried out through the modulation process. The proposed method can not only retain the advantage of fast dynamic response, but realize the minimization of power tracking error. Both simulation and experimental results verify the effectiveness and correctness of the proposed method.
Key wordsAC-DC converter      model predictive control      switching state function      power tracking error     
Received: 14 July 2017      Published: 30 October 2018
PACS: TM46  
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Yang Xingwu
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Yang Xingwu,Niu Mengjiao,Li Hao等. Improved Model Predictive Control Based on Switching State Function Calculation[J]. Transactions of China Electrotechnical Society, 2018, 33(20): 4834-4844.
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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.171018     OR     https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I20/4834
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