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Modeling and identification of the Jet Propulsion Laboratory vibratory rate microgyroscope.

机译:喷气推进实验室振动速率微型陀螺仪的建模和识别。

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摘要

This dissertation presents the experimental modeling and system identification of the Jet Propulsion Laboratory MEMS vibratory rate gyroscope. The primary objective is to estimate the modal frequencies, damping ratios, and the orientation of the vibrational nodes for important sensor dynamic modes with respect to the electrode-pick-offs in the sensor. An adaptive lattice filter is initially used to identify a high-order two-input/two-output transfer function describing the dynamics of the sensor in the neighborhood of lightly damped degrees of freedom. A three-mode model is then developed from the identified input/output model to determine the nodal axes' orientation. The identified model, which is extracted from several seconds of input/output data, also yields the frequency split between the sensor's modes that are exploited in detecting the rotation rate. The nodal axes' orientation and modal frequency split give direct insight into the source of quadrature measurement error that corrupts detection of the sensor's angular rate.; A new frequency-domain identification technique that estimates the mass, damping, and stiffness matrices based on an “impedance” model, is also investigated. A normalized coprime factor controller is synthesized to add damping to the dominant sensor modes using velocity feedback for efficient generation of frequency response data via the correlation method. Two identification methods are performed: (1) a least-squares approximation that minimizes the Frobenius norm of the error and, (2) a minimax optimization problem that minimizes the maximum singular value of the error on a frequency-by-frequency basis. The advantage of the second method is that the positive definiteness of the mass, damping, and stiffness matrices is guaranteed. The two methods give similar estimates of the nodal axes' orientations and are comparable to the time-domain sensor model and optical interferometric images.
机译:本文介绍了喷气推进实验室MEMS振动速率陀螺仪的​​实验建模和系统辨识。主要目的是针对传感器中重要的传感器动态模式,估算模态频率,阻尼比和振动节点的方向。自适应晶格滤波器最初用于识别高阶二输入/二输出传递函数,该函数描述了在轻阻尼自由度附近的传感器动态。然后从识别出的输入/输出模型中开发出三模式模型,以确定节点轴的方向。从几秒钟的输入/输出数据中提取出的识别出的模型,还会产生传感器模式之间的频率分割,这些模式用于检测转速。节点轴的方向和模态频率分割可直接洞察正交测量误差的来源,而正交测量误差会破坏传感器角速率的检测。还研究了一种新的频域识别技术,该技术可基于“阻抗”模型估算质量,阻尼和刚度矩阵。合成归一化的互质因子控制器,以使用速度反馈通过相关方法有效生成频率响应数据,从而将阻尼添加到主导传感器模式中。执行了两种识别方法:(1)最小二乘逼近最小化误差的Frobenius范数,(2)最小最大优化问题,逐个频率最小化误差的最大奇异值。第二种方法的优点是可以保证质量,阻尼和刚度矩阵的正定性。两种方法都可以对节点轴的方向进行类似的估算,并且可以与时域传感器模型和光学干涉仪图像进行比较。

著录项

  • 作者

    Hui, Jason Kwong-Ping.;

  • 作者单位

    University of California, Los Angeles.;

  • 授予单位 University of California, Los Angeles.;
  • 学科 Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 117 p.
  • 总页数 117
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;
  • 关键词

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