Thông tin tài liệu
Thông tin siêu dữ liệu biểu ghi
Trường DC | Giá trị | Ngôn ngữ |
---|---|---|
dc.contributor.author | Duan, J. | vi |
dc.contributor.other | Ou, Y. | vi |
dc.contributor.other | Hu, J. | vi |
dc.contributor.other | Wang, Z. | vi |
dc.contributor.other | Jin, S. | vi |
dc.contributor.other | Xu, C. | vi |
dc.date.accessioned | 2020-12-01T09:18:41Z | - |
dc.date.available | 2020-12-01T09:18:41Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://tailieuso.tlu.edu.vn/handle/DHTL/9821 | - |
dc.description.abstract | Abstract—The approach of dynamical system (DS) is promising for modeling robot motion, and provides a flexible means of realizing robot learning and control. Accuracy, stability, and learning speed are the three main factors to be considered when learning robot movements from human demonstrations with DS. Some approaches yield stable dynamical systems, but these may result in a poor reproduction performance, while some approaches yield good reproduction performance but are quite complex and timeconsuming. In this paper, we address the accuracy-stability-speed issues simultaneously. We present a learning method named the fast and stable modeling for dynamical systems, which is based on the extreme learning machine to efficiently and accurately learn the parameters of the DS as well as to ensure the asymptotic stability at the target. We confirm the proposed approach by performing both 2-D tasks of learning handwriting motions and a set of robot experiments. | vi |
dc.language | en_US | vi |
dc.publisher | IEEE Xplore | vi |
dc.relation.ispartofseries | IEEE Transactions on Systems, Man, and Cybernetics: Systems, (2019), VOL. 49, NO. 6, pp 1175-1185 | vi |
dc.subject | Extreme learning machine (ELM) | vi |
dc.subject | learn from demonstrations | vi |
dc.subject | learn from demonstrations | vi |
dc.subject | stability analysis | vi |
dc.title | Fast and Stable Learning of Dynamical Systems Based on Extreme Learning Machine | vi |
dc.type | BB | vi |
Trong bộ sưu tập: | Tài liệu hỗ trợ nghiên cứu khoa học |
Danh sách tệp tin đính kèm:
Bạn đọc là cán bộ, giáo viên, sinh viên của Trường Đại học Thuỷ Lợi cần đăng nhập để Xem trực tuyến/Tải về
Khi sử dụng tài liệu trong thư viện số bạn đọc phải tuân thủ đầy đủ luật bản quyền.