分数阶Boost变换器的两种预测电流控制
作者:
作者单位:

河南理工大学电气工程与自动化学院

作者简介:

通讯作者:

中图分类号:

TM46

基金项目:

国家自然科学基金项目(61703145)


Two Predictive Current Controls for Fractional Boost Converters
Author:
Affiliation:

College of Electrical Engineering and Automation, Henan Polytechnic University

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    基于分数阶微积分理论以及实际电容和实际电感在本质上是分数阶的事实.首先,在建立Boost变换器的分数阶数学模型基础上,提出分数阶预测电流控制,设计预测控制器.其次,在考察分数阶Boost电路的电感电流波形的基础上,提出分数阶Boost电路整数阶预测电流控制.最后,依据分抗链及Oustaloup分数阶近似算法,得到了分数阶电感逼近电路,利用Matlab软件对所设计的控制器进行仿真验证.结果表明,分数阶预测电流控制下的超调最小,过渡时间最短,尤其是在抗负载扰动上的性能更佳.整数阶预测电流控制的性能虽然低于分数阶预测控制,但也有较好的控制性能.同时仿真结果验证了所提控制方法的可行性和有效性.

    Abstract:

    Based on the theory of fractional calculus and the fact that actual capacitance and actual inductance are fractional in nature. Firstly,based on the establishment of a fractionalorder mathematical model of the Boost converter, a fractionalorder predictive current control is proposed, and a predictive controller is designed. Secondly, based on the investigation of the inductor current waveform of the fractional boost circuit, an integerorder predictive current control of the fractional boost circuit is proposed. Finally, a fractionalorder inductance approximation circuit was obtained based on the fractional reactance chain and the Oustaloup fractionalorder approximation algorithm. The designed controller was simulated and verified using Matlab software. The results show that the fractionalorder prediction current control has the smallest overshoot and the shortest transition time, especially the performance on antiload disturbance is better. Although the performance of integerorder predictive current control is lower than that of fractionalorder predictive control, it also has better control performance,the simulation results verify the feasibility and effectiveness of the proposed control method as well.

    参考文献
    相似文献
    引证文献
引用本文

引用本文格式: 王允建,霍星星,张 伟. 分数阶Boost变换器的两种预测电流控制[J]. 四川大学学报: 自然科学版, 2021, 58: 023002.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2019-11-13
  • 最后修改日期:2020-05-02
  • 录用日期:2020-05-05
  • 在线发布日期: 2021-04-02
  • 出版日期:
通知
自2024年3月6日起,《四川大学学报(自然科学版)》官网已迁移至新网站:https://science.scu.edu.cn/,此网站数据不再更新。
关闭