文化大學機構典藏 CCUR:Item 987654321/28407
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 47249/51115 (92%)
造访人次 : 14482683      在线人数 : 1339
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻
    主页登入上传说明关于CCUR管理 到手机版


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://irlib.pccu.edu.tw/handle/987654321/28407


    题名: 磁浮系統之智慧型控制
    Intelligent Control for Magnetic Levitation System
    作者: 阮胡洪
    贡献者: 機械工程學系數位機電碩士班
    关键词: Magnetic levitation system (Maglev)
    sliding mode control (SMC)
    sliding mode control using radial basic function network (SMCRBFN)
    日期: 2014
    上传时间: 2014-10-06 13:18:45 (UTC+8)
    摘要: 本文提出了一种控制磁悬浮系统(磁悬浮)不确定性的方法。为了实现精确的控制系统,基于神经网络的智能控制系统,提出补偿的不确定性。首先,磁悬浮系统的动态模型被建立。第二,滑动模式控制(SMC)被用于补偿发生在磁悬浮系统中的不确定性。所施加的控制器保证了系统的稳定性。此外,为了增加坚固性和释放约束的不确定性的要求,使用径向基函数网络(SMCRBFN)的滑动模式控制的建议。的成效,通过仿真和实验结果验证
    This thesis presents an approach to control the magnetic levitation system (Maglev) with uncertainty. To achieve precise control system, a neural network based intelligent control system was proposed to compensate the uncertainties. First, the dynamic model of a magnetic levitation system was built. Second, a sliding mode control (SMC) was applied to compensate the uncertainties that occurred in the magnetic levitation system. The applied controller guarantees the stability of the system. Moreover, to increase the robustness and to release the requirement of the uncertainty bound, a sliding mode control using a radial basic function network (SMCRBFN) is proposed. The effectiveness was verified through the simulation and experimental results.
    显示于类别:[機械工程系暨機械工程學系數位機電研究所] 博碩士論文

    文件中的档案:

    没有与此文件相关的档案.



    在CCUR中所有的数据项都受到原著作权保护.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈