Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes

doi:10.1007/s11633-021-1308-x

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > International Journal of Automation and Computing

	Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes
	Wilmer Ariza Ramirez 1
刊名	International Journal of Automation and Computing
	2021
卷号	18 期号:5 页码:681-693
关键词	Dependent Gaussian processes dynamic system identification multi-output Gaussian processes non-parametric identification autonomous underwater vehicle (AUV)
ISSN号	1476-8186
DOI	10.1007/s11633-021-1308-x
英文摘要	Non-parametric system identification with Gaussian processes for underwater vehicles is explored in this research with the purpose of modelling autonomous underwater vehicle (AUV) dynamics with a low amount of data. Multi-output Gaussian processes and their aptitude for modelling the dynamic system of an underactuated AUV without losing the relationships between tied outputs are used. The simulation of a first-principle model of a Remus 100 AUV is employed to capture data for the training and validation of the multi-output Gaussian processes. The metric and required procedure to carry out multi-output Gaussian processes for AUV with 6 degrees of freedom (DoF) is also shown in this paper. Multi-output Gaussian processes compared with the popular technique of recurrent neural network show that multi-output Gaussian processes manage to surpass RNN for non-parametric dynamic system identification in underwater vehicles with highly coupled DoF with the added benefit of providing the measurement of confidence.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/45457]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.Australian Maritime College, University of Tasmania, Newnham 7248, Australia 2.Jožef Steftan Institute, Ljubljana SI-1000, Slovenia 3.School of Engineering and Management, University of Nova Gorica, Vipara SI-5271, Slovenia
推荐引用方式 GB/T 7714	Wilmer Ariza Ramirez. Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes[J]. International Journal of Automation and Computing,2021,18(5):681-693.
APA	Wilmer Ariza Ramirez.(2021).Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes.International Journal of Automation and Computing,18(5),681-693.
MLA	Wilmer Ariza Ramirez."Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes".International Journal of Automation and Computing 18.5(2021):681-693.