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	Incremental echo state network for a water-jet propulsion USV: Theoretical and experimental research
	Li DC(李德才); He YQ(何玉庆)
	2016
会议名称	2016 American Control Conference, ACC 2016
会议日期	July 6－8, 2016
会议地点	Boston, MA, United states
页码	5296-5301
通讯作者	李德才
中文摘要	In this paper, a new system identification method is proposed. Since the new method combines the advantage of Kalman filter, l1 norm regularization and echo state mechanisms, it termed as ESNKF-l1. The ESNKF-l1 inherits the basic idea of ESN learning with Kalman filter to update model parameters online and utilize l1 norm regularization to obtain a sparse model structure. Moreover, the training of the ESNKF-l1 is facilitated by employing a bound optimization algorithm, based on which, a proper surrogate function is defined and the l1 norm regularization is approximated by l2 norm, while remaining constrains to the model parameters. It lead to an efficient method for model parameters estimation, which can be solved by using pseudo-observation (PO) method. In this case, the l2 norm is incorporated into the filtering process by designing a fictitious measurement function and the model parameters can be updated in an iteration manner. Experimental results show that the proposed method is suitable to capture the dynamics of USV and is superior to existing methods.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议主办者	Adaptics; et al.; GE Global Research; MathWorks; Mitsubishi Electric Research Laboratory (MERL); Quanser
会议录	Proceedings of the American Control Conference
会议录出版者	IEEE
会议录出版地	NEW YORK
语种	英语
ISSN号	0743-1619
ISBN号	978-1-4673-8682-1
WOS记录号	WOS:000388376105059
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/19364]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	Li DC,He YQ. Incremental echo state network for a water-jet propulsion USV: Theoretical and experimental research[C]. 见:2016 American Control Conference, ACC 2016. Boston, MA, United states. July 6－8, 2016.

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