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使用子空间方法识别哈默斯坦系统及其在踝关节刚度中的应用。

Identification of Hammerstein systems using subspace methods with applications to ankle joint stiffness.

作者信息

Zhao Yong, Kearney Robert E

机构信息

Department of Biomedical Engineering, McGill University, Montreal, QC, Canada, H3A 2B4.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:4367-70. doi: 10.1109/IEMBS.2009.5333593.

Abstract

A Hammerstein system is a series connection of a static non-linearity followed by a linear dynamic system. The subspace method is an efficient alternate to the classic Prediction Error Method to identify linear time invariant systems, especially those with multiple inputs and/or outputs. Furthermore, the subspace method has been extended to identify block-structured, nonlinear systems including those with Wiener and Hammerstein structures. This paper reviews the extended subspace method for the identification of Hammerstein systems, and demonstrates how it can be used to estimate dynamic joint stiffness. Simulation results demonstrate that the algorithm estimates the linear and nonlinear components of the ankle joint stiffness accurately.

摘要

哈默斯坦系统是一个由静态非线性环节后跟一个线性动态系统组成的串联系统。子空间方法是识别线性时不变系统,特别是那些具有多个输入和/或输出系统的经典预测误差方法的一种有效替代方法。此外,子空间方法已被扩展用于识别包括具有维纳和哈默斯坦结构的块结构非线性系统。本文回顾了用于识别哈默斯坦系统的扩展子空间方法,并展示了如何用它来估计动态关节刚度。仿真结果表明该算法能准确估计踝关节刚度的线性和非线性分量。

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