Predictive Current Control for Three Phase Induction Machine Using Multi-Steps Prediction Horizon
Wang Zhiguo1,2, Zheng Zedong1, Li Yongdong1,3, Li Guibin3
1. State Key Laboratory of Power System Department of Electrical Engineering Tsinghua University Beijing 100084 China; 2. Department of Control Engineering Academy of Army Armored Force Beijing 100072 China; 3. School of Electrical Engineering Xinjiang University Urumqi 830047 China
Abstract：Model predictive control (MPC) has several important advantages such that concepts are very intuitive and the multivariable case with constraints can be easily considered. So, MPC has become a hot research topic in electric drives. A predictive current control method based on continuous control set MPC (CCS-MPC) is investigated in this paper for the vector control of three phase induction machine. Firstly, the augment model of three phase induction machine is established based on voltage equation in synchronous coordinate system with rotor flux orientation. After that, the offset-free predictive current control method is presented. Secondly, the determining method of horizon length and weighting factors is researched by using the closed-loop poles of the system. And then, parameter robustness of the predictive current control is discussed. This paper presents how to use the augment model to realize offset-free control which is the fundamental issue for the control method research. The paper focuses on the effect of horizon length and weighting factors on the closed-loop poles position and the determining method of these parameters. The experimental results show that the predictive current control method can completely replace PI regulator to realize asynchronous motor current control.
王治国, 郑泽东, 李永东, 李贵彬. 三相异步电机电流多步预测控制方法[J]. 电工技术学报, 2018, 33(9): 1975-1984.
Wang Zhiguo, Zheng Zedong, Li Yongdong, Li Guibin. Predictive Current Control for Three Phase Induction Machine Using Multi-Steps Prediction Horizon. Transactions of China Electrotechnical Society, 2018, 33(9): 1975-1984.
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2018, Vol. 33 
