轮椅动力学的贝叶斯LPV-FIR辨识

2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) Pub Date : 2019-09-01 DOI:10.23919/SICE.2019.8859813

Y. Fujimoto, Tatsuki Tokushige, M. Nagahara

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引用次数: 1

摘要

本文以数据驱动的方式构建了轮椅动力学模型。我们特别关注轮椅的向前运动，为此我们采用了线性参数变化有限脉冲响应(LPV-FIR)模型。为了避免过拟合行为，我们采用了贝叶斯估计方法。实验结果表明，所构建的模型比线性模型更能准确地再现观测数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Bayesian LPV-FIR Identification of Wheelchair Dynamics

This paper constructs a model of wheelchair dynamics in a data-driven manner. In particular, we focus on the forward movement of the wheelchair, for which we adopt a Linear-Parameter-Varying Finite-Impulse-Response (LPV-FIR) model. To avoid the overfitting behavior, we employ the Bayesian estimation method. We show by experimental results that the constructed model reproduces the observed data more precisely than linear models.

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2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)

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