[1]汪先兵,费树岷,彭靳,等.模糊神经网络全闭环调控的永磁真空断路器动态特性分析[J].东南大学学报(自然科学版),2015,45(4):683-689.[doi:10.3969/j.issn.1001-0505.2015.04.013]
 Wang Xianbing,Fei Shumin,et al.Analysis of dynamic characteristic of PM vacuum circuit breaker based on fuzzy neural network full closed-loop control[J].Journal of Southeast University (Natural Science Edition),2015,45(4):683-689.[doi:10.3969/j.issn.1001-0505.2015.04.013]
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模糊神经网络全闭环调控的永磁真空断路器动态特性分析()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
45
期数:
2015年第4期
页码:
683-689
栏目:
电气工程
出版日期:
2015-07-20

文章信息/Info

Title:
Analysis of dynamic characteristic of PM vacuum circuit breaker based on fuzzy neural network full closed-loop control
作者:
汪先兵12费树岷1彭靳2金敏毅3薛涵3赵鹤3
1东南大学自动化学院, 南京210096; 2滁州学院电子与电气工程学院, 滁州239000; 3法泰电器(江苏)有限公司, 苏州215031
Author(s):
Wang Xianbing1 2 Fei Shumin1 Peng Jin2 Jin Minyi3 Xue Han3 Zhao He3
1 School of Automation, Southeast University, Nanjing 210096, China
2 School of Electronic and Electrical Engineering, Chuzhou University, Chuzhou 239000, China
3 Fatai Electric Appliance(Jiangsu)Co., Ltd., Suzhou 215031, China
关键词:
断路器 模糊神经网络 全闭环调控 动态特性
Keywords:
circuit breaker fuzzy neural network full closed-loop control dynamic characteristic
分类号:
TM561
DOI:
10.3969/j.issn.1001-0505.2015.04.013
摘要:
针对难以精确实现对永磁真空断路器合分闸过程动态特性控制,从而导致影响其机械与电气寿命的问题,提出了一种模糊神经网络全闭环智能调控方法.在分析永磁真空断路器合分闸过程硬件结构设计模型的基础上,建立了运动机构的实时位移x和输出量PWM占空比的隶属度函数与模糊控制规则.构造了1-3-1的三层BP神经网络结构,建立了合分闸过程BP神经网络数学模型,结合Matlab仿真软件训练了模糊控制规则,训练结果能较好满足系统合分闸过程精确控制要求.实验数据对比表明,相较于全导通控制策略和模糊控制策略,模糊神经网络控制策略能更有效地实现对永磁真空断路器合分闸过程的动态控制,提高了永磁真空断路器的机械与电气寿命.
Abstract:
It is difficult to realize precise dynamic control of opening and closing processes of the permanent magnet(PM)vacuum circuit breaker, which influences its mechanical and electrical lifetime. A fuzzy neural network full closed-loop intelligent control method is proposed to solve this problem. Based on the analysis of the hardware structure design model for the opening and closing processes of the PM vacuum circuit breaker, membership function between real-time displacement and output PWM(pulse width modulation)duty ratio and fuzzy control rules are established. A 1-3-1 three-layer BP(back propagation)neural network structure and the BP neural network mathematical model of the opening and closing processes are constructed. Matlab simulation software is employed to train and obtain fuzzy control rules, and the training results can well meet the precise control requirements during the opening and closing processes. The test data shows that, compared with fully-conducting control strategy and fuzzy control strategy, the fuzzy neural network control strategy can more efficiently realize the dynamic control of opening and closing processes of the PM vacuum circuit breaker, and further improve the mechanical and electrical lifespan of the PM vacuum circuit breaker.

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备注/Memo

备注/Memo:
收稿日期: 2014-12-10.
作者简介: 汪先兵(1981—),男,博士,讲师,seueelab_wxb@163.com.
基金项目: 国家自然科学基金资助项目(51307011)、安徽省自然科学基金资助项目(1308085QE97)、江苏省博士后科研资助计划资助项目(1301173C)、安徽省高校省级优秀人才基金资助项目(2013SQRL093ZD)、滁州学院科研资助项目(2012kj009B).
引用本文: 汪先兵, 费树岷, 彭靳,等.模糊神经网络全闭环调控的永磁真空断路器动态特性分析[J].东南大学学报:自然科学版,2015,45(4):683-689. [doi:10.3969/j.issn.1001-0505.2015.04.013]
更新日期/Last Update: 2015-07-20