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Improvement of induction motor performance at low speeds using fuzzy logic adaptation mechanism based sensorless direct field oriented control and fuzzy logic controllers (FDFOC)

机译:使用基于无传感器直接磁场定向控制和模糊逻辑控制器(FDFOC)的模糊逻辑自适应机制提高低速感应电动机的性能

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This paper presents a more relevant infrastructure: fuzzy sensorless direct field oriented control (FDFOC), compared to the usual sensorless direct field oriented control (DFOC), in order to improve the induction motor (IM) performance at low speeds. In the FDFOC, a fuzzy logic adaptation mechanism based Luenberger observer used for speed adaptation is adopted, and all the proportional-integral (PI) controllers are substituted for intelligent ones: fuzzy logic controllers (FLCs). In the interest of evaluating both systems performance FDFOC and DFOC, a detailed comparative study is presented: functioning in both motor rotation directions with application of load torque disturbance at low speeds. Simulation tests prove the robustness of the new infrastructure FDFOC in comparison with the usual DFOC: Quick response, good load torque rejection, decrease of the stator phase current on startup, as a result the system dynamic has been improved significantly. On the other hand, the simulation presents excellent speed observation using adaptive Luenberger observer (ALO) whereas the estimated speed perfectly pursues the reference at low speeds. Simulations are done using Matlab.
机译:本文提出了一个更相关的基础结构:与通常的无传感器直接磁场定向控制(DFOC)相比,模糊无传感器直接磁场定向控制(FDFOC)旨在提高低速下的感应电动机(IM)性能。在FDFOC中,采用了基于Luenberger观测器的模糊逻辑自适应机制进行速度自适应,并且所有比例积分(PI)控制器都被替换为智能控制器:模糊逻辑控制器(FLC)。为了评估两个系统的性能FDFOC和DFOC,提出了一个详细的比较研究:在低速时应用负载转矩扰动在两个电动机旋转方向上起作用。仿真测试证明了新基础设施FDFOC与常规DFOC相比的鲁棒性:快速响应,良好的负载转矩抑制,启动时定子相电流的减少,因此系统的动态性能得到了显着改善。另一方面,该仿真使用自适应Luenberger观测器(ALO)表现出了极好的速度观测,而估算的速度则完美地跟踪了低速时的参考。仿真是使用Matlab完成的。

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