Adaptive Neuro-Fuzzy Inference System based speed controller for brushless DC motor

被引：80

作者：

Premkumar, K. ^{[1
]}

Manikandan, B. V. ^{[2
]}

机构：

[1] Pandian Saraswathi Yadav Engn Coll, Dept Elect & Elect Engn, Sivagangai 630561, Tamil Nadu, India

[2] Mepco Schlenk Engn Coll, Dept Elect & Elect Engn, Sivakasi 626005, Tamil Nadu, India

来源：

NEUROCOMPUTING | 2014年 / 138卷

关键词：

BLDC motor; Mathematical model of the BLOC motor; Proportional Integral controller; Fuzzy Variable Structure controller; Fuzzy Tuned PID controller; ANFIS controller; DRIVES;

D O I：

10.1016/j.neucom.2014.01.038

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a novel controller for brushless DC (BLDC) motor has been presented. The proposed controller is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and the rigorous analysis through simulation is performed using simulink tool box in MATLAB environment. The performance of the motor with proposed ANFIS controller is analyzed and compared with classical Proportional Integral (PI) controller, Fuzzy Tuned PID controller and Fuzzy Variable Structure controller. The dynamic characteristics of the brushless DC motor is observed and analyzed using the developed MATLAB/simulink model. Control system response parameters such as overshoot, undershoot, rise time, recovery time and steady state error are measured and compared for the above controllers. In order to validate the performance of the proposed controller under realistic working environment, simulation result has been obtained and analyzed for varying load and varying set speed conditions. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：260 / 270

页数：11

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