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Implementation of a new fuzzy vector control of induction motor

机译:一种新型的异步电动机模糊矢量控制的实现

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The aim of this paper is to present a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of model uncertainties. Indeed, the presence of the uncertainties led us to use human expertise such as the fuzzy logic techniques. In order to maintain the decoupling and to overcome the problem of the sensitivity to the parametric variations, the field-oriented control is replaced by a new block control. The simulation results show that the both control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the fuzzy vector control provides the insensitivity to the parametric variations compared to the classical one. The fuzzy vector control scheme is successfully implemented in real-time using a digital signal processor board dSPACE 1104. The efficiency of this technique is verified as well as experimentally at different dynamic operating conditions such as sudden loads change, parameter variations, speed changes, etc. The fuzzy vector control is found to be a best control for application in an induction motor.
机译:本文的目的是提出一种使用1型模糊逻辑控制感应电动机的新方法。感应电动机具有非线性模型,不确定性和强耦合性。基于感应电动机逆模型的矢量控制技术解决了耦合问题。不幸的是,由于模型的不确定性,实际上没有对此进行检查。确实,不确定性的存在使我们不得不使用诸如模糊逻辑技术之类的人类专业知识。为了保持去耦并克服对参数变化的敏感性问题,以新的块控制代替了磁场定向控制。仿真结果表明,两种控制方案在其基本配置中均具有可比的解耦性能。但是,与经典变量控制相比,模糊矢量控制对参数变化不敏感。模糊矢量控制方案已使用数字信号处理器板dSPACE 1104成功地实时实施。在不同的动态操作条件下(例如突然的负载变化,参数变化,速度变化等),该技术的效率也得到了验证。发现模糊矢量控制是用于感应电动机的最佳控制。

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