无刷直流电机调速系统神经网络逆控制

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (572 KB)
输出: BibTeX | EndNote (RIS)

摘要无刷直流电机运行中参数摄动和换相过程的非线性, 在一定程度上限制了其调速性能。针对这些特点, 在分析无刷直流电机换相区和传导区数学模型的基础上, 提出了一种基于神经网络逆的控制策略, 采用静态神经网络加积分器来构造电机的逆系统, 并将该逆系统与原电机系统串联复合构成伪线性系统, 实现整体的近似线性化, 从而简化了外环控制器的设计难度。仿真与实验结果均表明神经网络逆控制方法对负载扰动与电机参数摄动有较强的鲁棒性, 且能在减小转速超调的同时保证了响应速度及跟踪精度, 使整个系统具有优良的动静态性能。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	刘国海
	金鹏
	魏海峰

关键词 ：无刷直流电机, 人工神经网络, 逆系统, 线性化

Abstract：Variation of parameters and nonlinear commutation process limit the speed control performance of brushless DC motor(BLDCM). A control approach based on neural network inverse system was developed for the brushless DC motor by analyzing the mathematical model in conduction region and commutation region. The inverse system of BLDCM consists of a static artificial neural network (ANN) and two integrators. By cascading the inverse system with BLDCM, the nonlinear system was transformed into pseudo-linear system and the whole system performance is improved. Simulation and experimental results show that the proposed scheme reduces overshoot, preserves fast speed response merit, and shows robust to load disturbance and motor parameters uncertainty. It effectively improves dynamic and static operation performance, and is a novel control method for BLDCM.

Key words： Brushless DC motor artificial neural network(ANN) inverse system linearization

收稿日期: 2009-06-24 出版日期: 2014-03-04

PACS:

TM383

基金资助:国家自然科学基金(60874014), 教育部博士点基金(20050299009)和江苏省自然科学基金(BK2007094)资助项目

作者简介: 刘国海男, 1964年生, 教授, 博士生导师, 从事电机控制, 复杂系统控制, 非线性智能控制等研究。金鹏男, 1984年生, 硕士研究生, 从事特种电机控制等研究.

引用本文:

刘国海, 金鹏, 魏海峰. 无刷直流电机调速系统神经网络逆控制[J]. 电工技术学报, 2010, 25(8): 24-30. Liu Guohai, Jin Peng, Wei Haifeng. Neural Network Inverse Control of Speed Variable System for BLDCM. Transactions of China Electrotechnical Society, 2010, 25(8): 24-30.

链接本文:

http://dgjsxb.ces-transaction.com/CN/Y2010/V25/I8/24

[1] 李钟明, 刘卫国. 稀土永磁电机[M]. 北京: 国防工业出版社, 1999.
[2] 叶长青, 尹华杰. 无刷直流电机速度的模糊控制方法[J]. 电气传动, 2006, 36(3): 3-7.
[3] Rubaai A, Ricketts D, Kankam M D. Laboratory implementation of a microprocessor-based fuzzy logic tracking controller for motion controls and drives[J]. IEEE Trans. on Industry Application, 2002, 38(2): 448-456.
[4] Kumar M, Singh B P. Fuzzy pre-compensated PI controller for PMBLDC motor drive[C]. International Conference on Power Electronics, Drives and Energy System, India, 2006.
[5] Hyeung Sik Choi, Yong Heon Park, Minho Lee. Global sliding-mode control improved design for a brushless DC motor[J]. IEEE Control System Magazine, 2001, 21(3): 27-35.
[6] Thirusakthimurugan P, Dananjayan P. A new generalized predictive controller for the speed control of PMBLDC motor[C]. Third International Conference on Information and Automation for Sustainability, Victoria, Australia, 2007.
[7] 刘国海, 刘平原, 等. 基于神经网络广义逆的两电机变频系统解耦控制的试验研究[J]. 中国电机工程学报, 2008, 28(36): 98-103.
[8] 戴先中, 刘国海, 张兴华. 恒压频比变频调速系统的神经网络逆控制[J]. 中国电机工程学报, 2005, 25(7): 109-114.
[9] 刘国海, 孙玉坤, 张浩, 等. 基于神经网络逆系统的磁悬浮开关磁阻电动机的解耦控制[J]. 电工技术学报, 2005, 20(9): 39-43.
[10] Dai Xianzhong, He Dan, Zhang Teng, et al. ANN generalized inversion for the linearization and coupling control of nonlinear systems[J]. IEE Proceeding Control Theory and Applications, 2003, 150(3): 267-277.
[11] 张晓峰, 胡庆波, 吕征宇. 基于Buck变换器的无刷直流电转矩脉动抑制方法[J]. 电工技术学报, 2005, 20(9): 73-76.
[12] 牛全民, 亓迎川. 基于状态观测器实现转速及负载转矩估计的直流调速系统[J]. 电子技术应用, 2000(5): 24-26.