Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Yunlang Xu"'
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 1, Pp 767-795 (2022)
Abstract Whale Optimization Algorithm (WOA), as a newly proposed swarm-based algorithm, has gradually become a popular approach for optimization problems in various engineering fields. However, WOA suffers from the poor balance of exploration and exp
Externí odkaz:
https://doaj.org/article/9be4a87fa4564400b26cb61ae09ac971
Publikováno v:
IET Control Theory & Applications, Vol 15, Iss 18, Pp 2344-2354 (2021)
Abstract Iterative learning control (ILC) has been widely used to improve motion performance when reference trajectories and external disturbances are strictly repetitive. However, the occurrence of non‐repetitive trajectories and disturbances woul
Externí odkaz:
https://doaj.org/article/16f7132dbc6d48afa257f9b4c6380409
Publikováno v:
ACS Omega, Vol 6, Iss 47, Pp 31765-31774 (2021)
Externí odkaz:
https://doaj.org/article/8865ee86b3fd4fee938076f26b7e9fc3
A Co-Optimization Method of Actuators/Sensors Placement and LQG Controller for Vibration Suppression
Publikováno v:
IEEE Access, Vol 9, Pp 29482-29489 (2021)
In the manufacturing industry, the high acceleration demands lead to the lightweight designs of the stages, while it may cause undesirable vibrations. In order to obtain the most efficient vibration suppression performance, this paper proposes a co-o
Externí odkaz:
https://doaj.org/article/9de4eca26c84457cbefe378566193f7b
Publikováno v:
IEEE Access, Vol 9, Pp 57385-57392 (2021)
In this paper, a multi-kernel neural network sliding mode control (MNNSMC) method is proposed to enhance the position tracking performance and disturbance suppression capability of permanent magnet linear synchronous motors (PMLSMs). The designed MNN
Externí odkaz:
https://doaj.org/article/d6beb34044ec43ad8803b456f8e1967d
Publikováno v:
Symmetry, Vol 14, Iss 9, p 1871 (2022)
The grey wolf optimization (GWO) algorithm is widely utilized in many global optimization applications. In this paper, a dynamic opposite learning-assisted grey wolf optimizer (DOLGWO) was proposed to improve the search ability. Herein, a dynamic opp
Externí odkaz:
https://doaj.org/article/2848d48022c14065a6ee23c3a82c2fce
Autor:
Yunlang, Xu1 (AUTHOR), Feng, Shu2 (AUTHOR), Xinyi, Su2 (AUTHOR), Liang, Guo2 (AUTHOR), Shuo, Han1 (AUTHOR), Xiaofeng, Yang1,2 (AUTHOR) xf_yang@fudan.edu.cn
Publikováno v:
Neural Computing & Applications. Jul2023, Vol. 35 Issue 21, p15877-15890. 14p.
Publikováno v:
International Journal of Precision Engineering and Manufacturing. 24:379-393
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d8957969bbca91b52279a2231a15ab2
https://doi.org/10.1007/s12541-022-00762-8
https://doi.org/10.1007/s12541-022-00762-8
Publikováno v:
ISA Transactions. 129:580-591
Uncertain dynamics and unknown time-varying disturbances always exist in servo systems and deteriorate tracking accuracy significantly. To tackle the problem, this paper presents a novel adaptive robust control scheme based on neural networks and the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02c2bf4c49af9089b93f8a8f290c565f
https://doi.org/10.1016/j.isatra.2021.12.026
https://doi.org/10.1016/j.isatra.2021.12.026
Publikováno v:
Nonlinear Dynamics. 108:1339-1356
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ec7ad14f55f06cf308f16cda871901e
https://doi.org/10.1007/s11071-022-07258-0
https://doi.org/10.1007/s11071-022-07258-0