基于神经网络广义逆的两电机变频系统内模控制

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Abstract For nonlinear high coupling two motor variable frequency systems (TMVFS), the dynamical BP neural network is firstly used to approximate to generalized inverse system of original system, then an internal model control (IMC) based on generalized inverse system method is proposed to this pseudo-linear system. Stability and robustness of the closed-loop system are proved, and its performances are analyzed. Finally, some relative experimental researches based on S7-300 PLC are studied. The results demonstrate that decoupling control with open-loop stability can be reached by neural network generalized inverse (NNGI) system method and the control performance of system can be ensured by inducting internal model control to subsystems.

Key words： Two motor systems BP neural network generalized inverse internal model control decoupling control robust stability

Received: 10 June 2008 Published: 04 March 2014

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TM351

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	Liu Guohai
	Yang Guanxue
	Shen Yue
	Chen Zhaoling

Cite this article:

Liu Guohai,Yang Guanxue,Shen Yue等. Internal Model Control of Two Motor Variable Frequency Systems Based on Neural Network Generalized Inverse[J]. Transactions of China Electrotechnical Society, 2010, 25(11): 56-61.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2010/V25/I11/56

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