时滞纳米运动系统的多速率采样预测自抗扰控制
Sampled-data predictive ADRC design for nano motion systems with measurement time delay
摘要点击 131  全文点击 156  投稿时间:2018-04-08  修订日期:2018-09-15
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DOI编号  10.7641/CTA.2018.80243
  2018,35(11):1560-1567
中文关键词  纳米控制  时滞  自抗扰控制  扩张状态观测器  采样控制
英文关键词  nano control  time-delay  active disturbance rejection control  extended state observer  sampled-data control
基金项目  国家自然科学基金项目(51775319), 科技部重点研发计划项目(2017YFF0105903), 苏州科技专项(SYG201718)资助.
学科分类代码  
作者单位邮编
田 川 北京航空航天大学 100191
闫 鹏 北京航空航天大学 100191
中文摘要
      电容型纳米位置传感器在纳米伺服系统中得到了越来越多的应用. 这类超高精度模拟传感器用于反馈信号时 因较长的模数转换时间将带来明显的测量时滞. 而这类数字纳米伺服系统也因硬件使其采样频率在处理高频干扰时受 到带宽限制. 本文针对测量时滞和高频干扰的挑战, 提出一种带采样预测功能的多速率自抗扰控制器设计方法. 首先建 立了电容式位移传感器的纳米运动平台带有时滞的动力学模型. 其次, 基于该模型设计多率采样预测线性扩张状态观测 器和多率反馈控制器. 通过设计预测型观测器, 适当选取观测器增益, 消除时滞对状态观测的影响. 另外, 将输出预估器 加入预测扩张状态观测器中重构采样点间系统输出值, 从而在时滞系统中更好地估计和消除高频干扰, 并给出了系统的 稳定性分析. 最后通过压电驱动纳米运动平台的实时控制实验验证本文提出控制器的有效性.
英文摘要
      Capacitive position sensors have been successfully applied in nano motion systems due to its ultra-high resolution. However, considerable time delay is inevitably introduced because of the high resolution AD conversion time. In addition, output sampling restrictions (such as sensor bandwidth) pose additional challenges for ultra-high servo control of such digital systems. To solve such problems, this paper presents a multi-rate predictive active disturbance rejection control architecture. The dynamical model with time delay for the nano stage is proposed. Based on the model, with which we design a sampled-data predictive automatic disturbances rejection control (ADRC) with inter-sample output prediction structure to construct inter-sample dynamics between two consecutive sampling instants, such that high frequency disturbances can be better rejected. The convergence of the estimation and the stability of the closed-loop system are analyzed based on Lyapunov-Krasovskii function method. Finally, effectiveness of the proposed control architecture is demonstrated by various real time experiments on a piezo-actuated nano motion stage, which outperforms existing control approaches.