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一种用于具有时变非线性的 Hammerstein 系统线性参数变化辨识的新算法。

A novel algorithm for linear parameter varying identification of Hammerstein systems with time-varying nonlinearities.

作者信息

Sobhani Tehrani Ehsan, Jalaleddini Kian, Kearney Robert E

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:4928-32. doi: 10.1109/EMBC.2013.6610653.

DOI:10.1109/EMBC.2013.6610653
PMID:24110840
Abstract

This paper describes a novel method for the identification of Hammerstein systems with time-varying (TV) static nonlinearities and time invariant (TI) linear elements. This paper develops a linear parameter varying (LPV) state-space representation for such systems and presents a subspace identification technique that gives individual estimates of the Hammerstein components. The identification method is validated using simulated data of a TV model of ankle joint reflex stiffness where the threshold and gain of the model change as nonlinear functions of an exogenous signal. Pilot experiment of TV reflex EMG response identification in normal ankle joint during an imposed walking task demonstrate systematic changes in the reflex nonlinearity with the trajectory of joint position.

摘要

本文描述了一种用于识别具有时变（TV）静态非线性和时不变（TI）线性元件的哈默斯坦系统的新方法。本文为此类系统开发了一种线性参数变化（LPV）状态空间表示，并提出了一种子空间识别技术，该技术可对哈默斯坦组件进行单独估计。使用踝关节反射刚度的时变模型的模拟数据对该识别方法进行了验证，其中模型的阈值和增益作为外生信号的非线性函数而变化。在施加的步行任务期间对正常踝关节的时变反射肌电图反应识别进行的初步实验表明，反射非线性随关节位置轨迹发生系统性变化。

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引用本文的文献

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Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions.
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