High Performance Adaptive Control for BLDC Motor with Real-Time Estimation of Uncertainties

Jin, Yufang; Tang, Zhangjun; Wen, Yangyang; Zou, Haifeng

doi:10.1109/apec.2006.1620760

Cited by 4 publications

(2 citation statements)

References 4 publications

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“…Bu nedenle FDAM hız kontrolüne yönelik olarak bir çok farklı kontrol yöntemi tasarlanmış ve literatürde sunulmuştur. Uyarlamalı kontrol ile [1], hibrit bulanık sinir ağı yapısı ile [2], genetik algoritma ve yapay sinir ağları ile [3], uyarlamalı ağ tabanlı bulanık mantık çıkarım ile [4], model referans uyarlamalı kontrol ile [5]- [7] FDAM hız kontrolü bu yöntemlere örnek olarak gösterilebilmektedir. Elektro-mekanik sistemlerin hız kontrolü için genellikle akım döngüsü ve hız döngüsü birbirinden ayrı düşünülmekte ve pratikte bu döngüler için oransal-integral (PI) kontrol yapıları kullanılmaktadır.…”

Section: Introductionunclassified

Adaptive backstepping controller design for the speed control of brushless DC Motor

Türker¹

2018

Pamukkale J Eng Sci

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Section: Introductionunclassified

Adaptive backstepping controller design for the speed control of brushless DC Motor

Türker¹

2018

Pamukkale J Eng Sci

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“…Direct Drive Actuator (DDA), which has such good features as high-frequency response, large flow highpower density and excellent anti-contamination characteristics, is extensively adopted in the research and application fields of modern industrial automation, military, chemical industry, aviation and aerospace, etc (Jin et al, 2006). Traditionally, DDA is actualized by hydraulic drive with complex mechanical transmission mechanism, which causes complexity in mechanical structure, bulkiness in volume, slow responses, low positioning precision and dynamic performance (Buchnik and Rabinovici, 2004).…”

Section: Introductionmentioning

confidence: 99%

Position Servo Control for a Direct-Drive Actuator Based on Genetic Algorithm

Liu¹,

Gao²

2013

RJASET

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A novel position control strategy for a Brushless DC motor (BLDC) drive is proposed in this paper. Brushless DC motor, which is widely used in the field of Direct Drive servo Actuator (DDA) with superior performance, possesses fast transient response and high accuracy. Nevertheless, there are such uncertainties as unpredictable flow torques and estimated errors of the BLDC model in this system, which may influence the accuracy and the rapid response of the control. So in this paper, genetic algorithm is applied to the position loop. Simultaneously, in order to improve the rapidness of the whole system, position and velocity double closed-loop system is compared with position and current double closed-loop system. Experimental results validate the scheme proposed can attenuate the influences by the uncertainties of the model sharply. The genetic algorithm used in the position loop can ensure the system's stability and the accuracy of the position response. While tracking the same step response the step rise time of the double closed loop structure of the position and current reduced more than 25% compared with that of the double closed loop structure of the position and velocity.

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Adaptive Speed Control for Brushless DC Motors Based On Genetic Algorithm and RBF Neural Network

Wang

Xia

Zhang

et al. 2007

2007 IEEE International Conference on Control and Automation

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High Performance Adaptive Control for BLDC Motor with Real-Time Estimation of Uncertainties

Cited by 4 publications

References 4 publications

Adaptive backstepping controller design for the speed control of brushless DC Motor

Adaptive backstepping controller design for the speed control of brushless DC Motor

Position Servo Control for a Direct-Drive Actuator Based on Genetic Algorithm

Adaptive Speed Control for Brushless DC Motors Based On Genetic Algorithm and RBF Neural Network

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