Modified internal model control of induction motor variable frequency speed control system in v/f mode based on neural network generalized inverse

Control and Decision Conference(2010)

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摘要
In order to improve the robustness and anti-interference ability of induction motor variable frequency speed control system (IMVFSCS), a modified internal model control (MIMC) method based on neural network generalized inverse (NNGI) was proposed. On the basis of reversibility analysis of original system, the generalized inverse model approximated by the dynamical BP neural network was cascaded with the original system. Based on the idea of NNGI, linearization and open-loop stability of system can be reached, which benefits the integration of control system. Then the robust stability can be improved by introducing modified internal model control method to generalized pseudo-linear system. The results of experimental researches demonstrate that the linearization of the system can be realized successfully and the high performance of speed control can be ensured when the system has inverse modeling errors and changeable load.
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关键词
machine control,modified internal model control,neural network,robustness,open-loop system stability,variable frequency speed control system,neurocontrollers,frequency control,neural network generalized inverse method,system linearization,generalized inverse,speed control system,pseudolinear system,robust control,modified internal model control method,induction motor,angular velocity control,reversibility analysis,induction motors,open loop systems,dynamical bp neural network,error correction,speed control,artificial neural networks,inverse modeling,control systems,linear system,inverse problems,frequency,neural networks,control system,mathematical model
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