基于AI的SRM驱动控制器和估计器的无载鲁棒性分析

Proceedings of the International Conference on Advances in Information Communication Technology & Computing Pub Date : 2016-08-12 DOI:10.1145/2979779.2979888

S. Bishnoi, R. Kumar, R. A. Gupta

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引用次数: 0

摘要

本文对采用四相8/6极开关磁阻电机(SRM)的人工智能(AI)驱动进行了空载鲁棒性分析。SR电机、基于人工智能的控制器(即模糊、ANN & ANFIS)和基于人工智能的角度估计器(即模糊、ANN & ANFIS)模型被开发并集成为模糊-模糊、ANNANN & ANFIS-ANFIS SRM驱动器。对驱动器进行了鲁棒性仿真，并对结果进行了比较。通过改变开关磁阻电机的物理参数，包括SRM模型中的相位绕组电阻(R)、阻尼常数(F)和转子惯量(J)，来测试驱动器的鲁棒性。通过对这些驱动器在空载条件下的仿真，获得了它们在启动和500转/分稳态条件下的鲁棒性性能。鲁棒性性能已被绘制并比较，以找出最鲁棒的基于AI的SRM驱动器。

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No load Robustness Analysis of AI Based Controllers & Estimators for SRM Drive

In this paper no-load robustness analysis of Artificial Intelligence (AI) based drives using four phases 8/6 poles Switched Reluctance Motor (SRM). Models of SR motor, AI based controllers i.e. fuzzy, ANN & ANFIS and AI based angle estimators i.e. fuzzy, ANN & ANFIS were developed and integrated as fuzzy-fuzzy, ANNANN & ANFIS-ANFIS SRM drives. Simulation of drives has been done for robustness performance of the drives and compared results. Robustness of drives are tested by varying switched reluctance motor physical parameters, including phase winding resistance (R), damping constant (F) and rotor inertia (J) in the SRM model. Robustness performance at startup and steady-state conditions at 500 rpm has been obtained by simulating these drives for no-load condition. Robustness performance has been plotted and compared to figure-out most robust AI based SRM drive.

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Proceedings of the International Conference on Advances in Information Communication Technology & Computing

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