Rafa Souad, Larabi Abdelkader, Barazane Linda, Manceur Malik, Essounbouli Najib, Hamzaoui Abdelaziz
CReSTIC, IUT of Troyes. University of Reims Champagne Ardenne. 9 Rue de Québec B.P. 396, Troyes cedex, France; The Industrial Electrical System, University of Science and Technology Houari Boumediene. USTHB, BP32 El Alia, Algeria.
The Industrial Electrical System, University of Science and Technology Houari Boumediene. USTHB, BP32 El Alia, Algeria.
ISA Trans. 2014 May;53(3):744-54. doi: 10.1016/j.isatra.2014.02.005. Epub 2014 Mar 12.
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.
本文的目的是提出一种使用一阶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，不确定且强耦合。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，在实际中由于模型不确定性，这一点并未得到验证。实际上，不确定性的存在促使我们使用诸如模糊逻辑技术这样的人类专业知识。为了保持去耦并克服对参数变化的敏感性问题，采用一种新的块控制取代了磁场定向控制。仿真结果表明，两种控制方案在其基本配置下，在去耦方面提供了可比的性能。然而，与传统的矢量控制相比，模糊矢量控制对参数变化不敏感。使用数字信号处理器板dSPACE 1104成功地实时实现了模糊矢量控制方案。该技术的有效性在不同动态运行条件下，如突然负载变化、参数变化、速度变化等，通过实验得到了验证。结果发现模糊矢量控制是感应电动机应用中的一种最佳控制方法。
