Robust Control Strategy for the Speed Control of Brushless DC Motor
Zhi Liu1, Bai-Fen Liu2
(1.School of Traffic and Transportation Engineering, Central South University, Changsha 400083, China;2.School of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang 330013, China)
Abstract:
Brushless DC motor (BLDCM) speed servo system is multivariable, nonlinear and strong coupling. The parameter variation, the cogging torque and the load disturbance easily influence its performance. Therefore, it is difficult to achieve superior performance by using the conventional PID controller. To solve the deficiency, the paper represents the algorithm of active-disturbance rejection control (ADRC) based on back-propagation (BP) neural network. The ADRC is independent on accurate system and its extended-state observer can estimate the disturbance of the system accurately. However, the parameters of Nonlinear Feedback (NF) in ADRC are difficult to obtain. So in this paper, these parameters are self-turned by the BP neural network. The simulation and experiment results indicate that the ADRC based on BP neural network can improve the performances of the servo system in rapidity, control accuracy, adaptability and robustness.
Key words: brushless DC motor (BLDCM) BP (back propagation algorithms) ADRC (active-disturbance rejection control) parameters self-turning.
DOI：10.11916/j.issn.1005-9113.2013.02.017
Clc Number:TM301.2
Fund:
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Robust Control Strategy for the Speed Control of Brushless DC Motor
本站小编 哈尔滨工业大学/2019-10-24
相关话题/Robust Control Strategy Speed Control
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