基于径向基函数神经网络的感应电机矢量控制

2007 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives Pub Date : 2007-12-04 DOI:10.1109/DEMPED.2007.4393097

M. Jokar, B. Abdi, M. Ardebili

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引用次数: 6

摘要

由于异步电动机的非线性和复杂的运行，特别是在瞬态静校正中，需要特殊的控制策略。通过对转速和转子磁链方程进行解耦并进行同步控制，实现了电机的最高效率和快速动态性能。当选择合适的磁链时，效率最高，并且由于转速与转子磁链方程的动态解耦，可以修改转子磁链以达到最高效率并使转速达到期望值。利用RBF神经网络对这些变化进行了精确控制。

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Vector Control of Induction Motors Using Radial Basis Function Neural Network

Due to nonlinear and complex operation, especially in transient statics, induction motors needs special control strategies. In this work, decoupling of speed and rotor flux equations and their simultaneous control are used to achieve the highest efficiency and fast dynamic performance. The highest efficiency is reached when the proper flux is selected and as a result of dynamic decoupling of speed and rotor flux equations, the rotor flux can be modified to achieve the highest efficiency and make the speed be at its desired value. The precise control of these changes has been done using RBF neural network.

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2007 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives

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