随机变批次长度的反馈辅助PD型量化迭代学习控制
作者:
作者单位:

1. 北京化工大学 信息科学与技术学院,北京 100029;2. 中国人民大学 数学学院,北京 100872;3. 辽宁科技大学 电子与信息工程学院,辽宁 鞍山 114051

作者简介:

通讯作者:

E-mail: jwang@mail.buct.edu.cn.

中图分类号:

TP273

基金项目:

国家自然科学基金项目(61973023,61573050,61673045);北京市自然科学基金项目(4202052).


Feedback-assisted PD-type quantized iterative learning control with randomly iteration varying lengths
Author:
Affiliation:

1. College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China;2. School of Mathematics,Renmin University of China,Beijing 100872,China;3. School of Electronic and Information Engineering,University of Science and Technology LiaoNing,Anshan 114051,China

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:

    针对离散线性系统,研究批次长度随机变化的反馈辅助PD型量化迭代学习控制问题.考虑系统信号经量化后传输到控制器或执行器的情况,给出两种量化方案:跟踪误差信号量化和控制输入信号量化.基于两种不同的量化信号,在批次长度和初始条件随机变化前提下设计反馈辅助PD型迭代学习控制算法.采用扇形界的处理方法和堆积系统框架,推导数学期望下的学习收敛条件:在误差信号量化情况下,所提出控制算法可以保证跟踪误差渐近收敛到零;在控制输入信号量化情况下,所提出控制算法能够保证跟踪误差有界收敛.仿真示例对比验证了两种量化方案下所提出方法的有效性和优越性.

    Abstract:

    The feedback-assisted PD-type quantized iterative learning control problem is studied for discrete linear systems with iteration-varying trial lengths. Considering that the system signal is transmitted to the controller or actuator after being quantized. Two quantization schemes are given, including tracking error signal quantization and control input signal quantization. In the case of iteration-varying trial lengths and iteration-varying initial state conditions, a feedback-assisted PD-type update law is developed based on the quantized signal. The learning convergence condition under mathematical expectations derived with the sector bound method and the lifting representation:tracking error signal quantization can obtain zero tracking error, and control input signal quantization only guarantee that the tracking error converges to a bound. Simulation examples are provided to demonstrate the effectiveness and superiority of the proposed scheme under the two quantization schemes.

    参考文献
    相似文献
    引证文献
引用本文

王晶,周楠,王森,等.随机变批次长度的反馈辅助PD型量化迭代学习控制[J].控制与决策,2021,36(10):2569-2576

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:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2021-08-18
  • 出版日期: 2020-10-20