• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (9): 165-170.

• 论文 • 上一篇    下一篇

粗精动运动平台的系统辨识激励信号优化设计

杨一博;尹文生;汪劲松;朱煜;蔡田   

  1. 清华大学精密仪器与机械学系;清华大学摩擦学国家重点实验室
  • 发布日期:2010-05-05

Optimal Excitation Signal Design for Identification of a Coarse-fine Motion Platform

YANG Yibo;YIN Wensheng;WANG Jinsong;ZHU Yu;CAI Tian   

  1. Department of Precision Instruments and Mechanology, Tsinghua University The State Key Laboratory of Tribology, Tsinghua University
  • Published:2010-05-05

摘要: 针对粗精动运动平台系统辨识中激励信号的生成进行了优化设计方法的研究。粗精动平台结构通常用于长行程、高精度的运动平台系统,如扫描光刻机运动平台、硬盘寻道平台等系统。获得粗精动系统的准确模型是改进粗精动运动系统控制的重要基础。而系统辨识是获得系统模型的一种有效方式。其中输入信号设计是系统辨识试验重要的一部分。将粗精动运动平台的系统模型简化为一类多变量有限阶次线性时不变模型;将多入多出(Multiple-input multiple-output,MIMO)辨识方法引入粗精动系统辨识,并提出一种多入多出模型系统辨识激励信号优化设计算法,算法通过将多正弦曲线时域信号与其功率谱密度参数化,利用参数化后的激励信号在有限功率输入下进行激励信号优化;理论分析与仿真结果表明此方法可以有效提高估计模型的渐进方差性能。

关键词: 粗精动, 激励信号, 系统辨识, 优化设计

Abstract: Identification excitation signal design method is improved for a coarse-fine motion platform. A coarse-fine platform structure is widely used in long stroke, high precision motion platform systems, such as scan lithography tool motion platform and hard disk track-seeking platform. Obtaining an accurate model of course-fine system is an important basis for improving the control of the system, while system identification is an effective way to obtain the system model, in which the design of input signal is an important part of the test of system identification. The system model of coarse-fine motion platform is simplified to a multivariable finite dimensional linear time invariant discrete-time model. Multiple-input multiple-output (MIMO) identification method is introduced into coarse-fine system identification. An optimization design algorithm of excitation signal of multiple-input multiple-output model system identification is proposed. The algorithm parameterizes the multi-sine curve time domain signal and its power spectrum density. Then the parameterized excitation signal is optimized under limited power output. The results of theoretical analysis and simulation show that this method can effectively improve the performance of asymptotic covariance of the estimation model.

Key words: Coarse-fine, Excitation signal, Optimization design, System identification

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