A novel data-driven input shaping method using residual impulse vector via unscented Kalman filter

doi:10.1016/j.knosys.2025.114385

	A novel data-driven input shaping method using residual impulse vector via unscented Kalman filter
	Yang, Weiyi 1; Li, Yuqi 2; Shang, Mingsheng 1; Li, Shuai 3,4; Wen, Shiping 5
	2025-11-04
发表期刊	KNOWLEDGE-BASED SYSTEMS
ISSN	0950-7051
卷号	329 页码:10
摘要	Driven by escalating demands for precision and speed in modern industrial applications, residual vibrations in flexible structures and underactuated systems have emerged as a critical technical challenge, particularly during high-speed emergency braking scenarios. Input shaping has proven to be an effective technique for vibration control. However, existing input shapers commonly encounter challenges with time delay and inaccurate parameters, leading to suboptimal control performance. To address these critical issues, this paper proposes an Unscented Kalman filter-based Residual negative equal-magnitude Shaping (URS) model with two-fold ideas: a) reducing the time delay and compensating the modeling error via the consideration of negative and residual impulse vector; and b) identifying system parameters using a data-driven unscented Kalman filter to enhance control effectiveness. To validate its performance, four experimental datasets from laboratory systems have been established and publicly released. Empirical studies demonstrate that the proposed URS model has achieved a significant vibration suppression effect over several state-of-the-art methods.
关键词	Input shaping System parameter identification Modeling error compensation Unscented Kalman filter Data driven vibration control
DOI	10.1016/j.knosys.2025.114385
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62272078]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:001583005000002
出版者	ELSEVIER
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41643
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wen, Shiping
作者单位	1.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.Univ Oulu, Fac Informat Technol & Elect Engn, Oulu 90570, Finland 4.VTT Technol Res Ctr Finland, Oulu 90570, Finland 5.Univ Technol, Australian AI Inst, Fac Engn & Informat Technol, Ultimo, Australia
推荐引用方式 GB/T 7714	Yang, Weiyi,Li, Yuqi,Shang, Mingsheng,et al. A novel data-driven input shaping method using residual impulse vector via unscented Kalman filter[J]. KNOWLEDGE-BASED SYSTEMS,2025,329:10.
APA	Yang, Weiyi,Li, Yuqi,Shang, Mingsheng,Li, Shuai,&Wen, Shiping.(2025).A novel data-driven input shaping method using residual impulse vector via unscented Kalman filter.KNOWLEDGE-BASED SYSTEMS,329,10.
MLA	Yang, Weiyi,et al."A novel data-driven input shaping method using residual impulse vector via unscented Kalman filter".KNOWLEDGE-BASED SYSTEMS 329(2025):10.