Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Qing‐yuan Xu"'
Publikováno v:
Electronics Letters, Vol 60, Iss 19, Pp n/a-n/a (2024)
Abstract To address the variable initial state and trail length this paper first presents a robust PD‐type open‐closed‐loop iterative learning control (ILC) law for a multiple‐input‐multiple‐output (MIMO) linear discrete‐time system. It
Externí odkaz:
https://doaj.org/article/ac51879744b4427fa6156382219a3412
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 8, Iss 3, Pp 645-660 (2023)
Abstract For linear time varying (LTV) multiple input multiple output (MIMO) systems with vector relative degree, an open‐closed‐loop iterative learning control (ILC) strategy is developed in this article, where the time interval of operation is
Externí odkaz:
https://doaj.org/article/14fabe184b5d496cb84c6c95b0824862
Publikováno v:
Cancer Medicine, Vol 12, Iss 3, Pp 3812-3829 (2023)
Abstract Background Diffuse large B‐cell lymphoma (DLBCL) is a non‐Hodgkin lymphoma with high mortality rates. Small nucleolar RNAs (snoRNAs) are tumor‐specific biological markers, but there are few studies on the role of snoRNAs in DLBCL. Mate
Externí odkaz:
https://doaj.org/article/ebd1c938154146b28dbf3f4be989553b
Publikováno v:
IEEE Access, Vol 10, Pp 125015-125026 (2022)
In the existing robust iterative learning control (ILC) for 2-D discrete systems, they typicallly require to satisfy a core hypothesis that the strict repetitiveness of tracking reference trajectory and system model should be satisfied. This paper fi
Externí odkaz:
https://doaj.org/article/2aac08dc59cb48ba96ff0e5402f6d415
Publikováno v:
Frontiers in Veterinary Science, Vol 10 (2023)
IntroductionPasteurella multocida is a widespread respiratory pathogen in pigs, causing swine pneumonia and atrophic rhinitis, and the capsular serogroups A and D are the main epidemic serogroups in infected animals. This study investigated the prote
Externí odkaz:
https://doaj.org/article/e32a2ac80de64df2beb46e29985fbb58
Autor:
Xin-Tu Lei, Qing-yuan Xu
Publikováno v:
Journal of King Saud University: Science, Vol 32, Iss 3, Pp 2074-2080 (2020)
For the purpose of evaluating scientific output, examining literature utilization, and predicting the direction of publication for Journal of King Saud University – Science (JKSU-S). This paper explored the hot topics and new trends through the sta
Externí odkaz:
https://doaj.org/article/cc0e2d2db1914d5c863ebdc62ff25544
Publikováno v:
IEEE Access, Vol 7, Pp 134920-134925 (2019)
Among the existing adaptive iterative learning control (ILC) work concerning unknown control direction problem, no result is available for the two-dimensional (2-D) dynamical systems. In this paper, an adaptive ILC is developed for a class of 2-D dyn
Externí odkaz:
https://doaj.org/article/cbabf7ff60e9416288c1a6c1c6e8eb5c
Publikováno v:
Mathematics, Vol 10, Iss 19, p 3462 (2022)
An adaptive fuzzy iterative learning control (ILC) algorithm is designed for the iterative variable reference trajectory problem of nonlinear discrete-time systems with input saturations and unknown control directions. Firstly, an adaptive fuzzy iter
Externí odkaz:
https://doaj.org/article/eb01b0b0f7da4a3a9fdc5954cf75f5a5
Autor:
Long-Zhen Lin, Qian-Wang Zheng, Tao Wei, Zi-Qian Zhang, Chao-Fan Zhao, Han Zhong, Qing-Yuan Xu, Jun-Fang Lin, Li-Qiong Guo
Publikováno v:
Frontiers in Microbiology, Vol 11 (2020)
The continuing emergence and development of pathogenic microorganisms that are resistant to antibiotics constitute an increasing global concern, and the effort in new antimicrobials discovery will remain relevant until a lasting solution is found. A
Externí odkaz:
https://doaj.org/article/9fb18d5f6e35434a8ccc0b3b19e00e24
Autor:
Yun-Shan Wei, Qing-Yuan Xu
Publikováno v:
Complexity, Vol 2018 (2018)
For linear discrete-time systems with randomly variable input trail length, a proportional- (P-) type iterative learning control (ILC) law is proposed. To tackle the randomly variable input trail length, a modified control input at the desirable trai
Externí odkaz:
https://doaj.org/article/5550770ed7654f74b42ebb7ed3445009