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首页> 外文期刊>International Journal of Automation and Control >Neural network inverse decoupling control of stator flux and torque for induction motor drives
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Neural network inverse decoupling control of stator flux and torque for induction motor drives

机译：感应电机驱动的定子磁链和转矩的神经网络逆解耦控制

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摘要

This paper focuses on the development of a stator flux and torque decoupling mechanism based on artificial neural network (ANN) inverse system for induction motor (IM). Firstly, the existence of the inverse system is approved by inverse system theory. However, the analytic inverse model is hardly applied in the engineering fields because it is excessively depends on the IM parameters. Therefore, the method of synthesising neuro-network and analytic function is suggested in this paper, and an ANN-based inverse decoupling control scheme is constructed in order to eliminate the coupling between stator flux and torque. To accelerate the convergence speed of neuro-network and enhance its generalisation ability, the non-linear operations are realised by the analytic operation method and the corresponding results act as the inputs of network. In addition, simulation results are provided to validate the effectiveness of the proposed scheme.
机译：本文着重研究了基于人工神经网络（ANN）感应电动机（IM）逆系统的定子磁链和转矩解耦机制。首先，逆系统的存在得到了逆系统理论的认可。然而，解析逆模型在工程领域中几乎没有应用，因为它过度依赖于IM参数。因此，本文提出了一种综合神经网络和解析函数的方法，并建立了一种基于神经网络的逆解耦控制方案，以消除定子磁链与转矩之间的耦合。为了加快神经网络的收敛速度并增强其泛化能力，通过解析运算方法实现了非线性运算，并将相应的结果作为网络的输入。此外，提供了仿真结果以验证所提出方案的有效性。

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