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首页> 外文学位 >Sliding mode state estimation for nonlinear discrete-time systems: Applications in image sequence analysis.
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Sliding mode state estimation for nonlinear discrete-time systems: Applications in image sequence analysis.

机译：非线性离散时间系统的滑模状态估计：在图像序列分析中的应用。

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摘要

A dynamical system, often implemented numerically, whose purpose is to estimate unmeasureable states based on available measurements of a dynamical process is called an observer. Novel methods, based on the theory of dynamical systems with sliding modes, are proposed and analyzed for state estimation of uncertain, nonlinear, discrete-time systems. The proposed discrete-time sliding mode observers retain the fundamental property, familiar in continuous-time sliding mode control literature, of robustness to dynamical modelling errors. Design methodologies are proposed for linear or nonlinear, non-redundant or redundant measurement models. Methods for redundant measurements provide an optimal fusion of the available data during the sliding mode through minimization of a squared error cost measure. New methods to obtain exponential stability of nonlinear discrete-time systems are introduced with applications in stability and robustness analysis of the proposed sliding mode observers. For nonlinear measurements, ideal observer forms are represented by systems of nonlinear integral equations which implicitly define the observer output. Practical implementation methodologies are proposed through development and analysis of local iterations at each measurement event. These local iterations for nonredundant or redundant measurements reduce, respectively, to Newton and modified Gauss-Newton methods for which there is a broad literature base. The resulting iterated sliding mode observers can be applied to a broad class of discrete-time state estimation problems. Applications and performance of the various sliding mode observer forms are demonstrated through simulation results in the problem of estimating motion and structure of manoeuvring objects based on feature position measurements in long multiple-camera image sequences.
机译：一个通常以数字方式实现的动态系统称为观察者，其目的是基于动态过程的可用度量来估计不可测状态。提出并分析了基于滑模动力学系统的新方法，并分析了不确定，非线性，离散时间系统的状态估计。所提出的离散时间滑模观测器保留了连续时间滑模控制文献所熟悉的对动态建模误差的鲁棒性的基本属性。提出了用于线性或非线性，非冗余或冗余测量模型的设计方法。冗余测量方法通过最小化平方误差成本测量值，在滑模期间提供了可用数据的最佳融合。介绍了获得非线性离散时间系统指数稳定性的新方法，并将其应用于所提出的滑模观测器的稳定性和鲁棒性分析中。对于非线性测量，理想的观测器形式由隐式定义观测器输出的非线性积分方程组表示。通过在每个测量事件处开发和分析局部迭代，提出了实用的实现方法。对于非冗余或冗余测量的这些局部迭代分别减少了具有广泛文献基础的牛顿法和改进的高斯-牛顿法。所得的迭代滑模观测器可以应用于广泛的离散时间状态估计问题。通过仿真结果证明了各种滑模观察器形式的应用和性能，该仿真结果基于在长多摄像机图像序列中基于特征位置测量来估计机动对象的运动和结构的问题。

著录项

  • 作者

    Aitken, Victor Charles.;

  • 作者单位

    Carleton University (Canada).;

  • 授予单位 Carleton University (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 1995
  • 页码 402 p.
  • 总页数 402
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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