Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Jianwan Ding"'
Publikováno v:
IEEE Access, Vol 12, Pp 92130-92141 (2024)
In recent years, physics-informed neural networks (PINNs) have developed significantly as a deep learning technology. In analogy to the selection of grid cells in traditional numerical methods, the distribution of sample points used for training PINN
Externí odkaz:
https://doaj.org/article/9788c16f0461454197eaca6378598ca9
Publikováno v:
Entropy, Vol 26, Iss 6, p 451 (2024)
Physics-informed neural networks (PINNs) have garnered widespread use for solving a variety of complex partial differential equations (PDEs). Nevertheless, when addressing certain specific problem types, traditional sampling algorithms still reveal d
Externí odkaz:
https://doaj.org/article/ec12997954c34626afc5238828334b37
Publikováno v:
Actuators, Vol 13, Iss 5, p 189 (2024)
Robotic manipulators play a pivotal role in modern intelligent manufacturing and unmanned production systems, often tasked with executing specific paths accurately. However, the input of the robotic manipulators is trajectory which is a path with tim
Externí odkaz:
https://doaj.org/article/435d91c15d0343358924f22a955b08ed
Publikováno v:
Applied Sciences, Vol 14, Iss 5, p 2219 (2024)
The introduction of a dynamic model in robot trajectory tracking control design can significantly improve its trajectory tracking accuracy, but there are many uncertainties in the robot dynamic model which can be dealt with through robust control and
Externí odkaz:
https://doaj.org/article/a85265b4c6b44369a6027a8bd570eebd
Publikováno v:
Applied Sciences, Vol 13, Iss 12, p 6973 (2023)
The artificial potential field method is a highly popular obstacle avoidance algorithm which is widely used in the field of industrial robotics due to its high efficiency. However, the traditional artificial potential field method has poor real-time
Externí odkaz:
https://doaj.org/article/4a9d7ef1b6584fe89a96aed3779575cf
Publikováno v:
Applied Sciences, Vol 12, Iss 13, p 6741 (2022)
The trajectory planning method with dynamics is the key to improving the motion performance of manipulators. The optimal control method (OCM) is a key technology to solve optimal problems with dynamics. There are direct and indirect methods in OCM; i
Externí odkaz:
https://doaj.org/article/8f15269d21094f65a3cd70b7d60a821c
Publikováno v:
Mathematics, Vol 9, Iss 21, p 2660 (2021)
Structural analysis is a method for verifying equation-oriented models in the design of industrial systems. Existing structural analysis methods need flattening of the hierarchical models into an equation system for analysis. However, the large-scale
Externí odkaz:
https://doaj.org/article/58e358c8d31a43ff8738fe237c7adb80
Publikováno v:
Symmetry, Vol 12, Iss 8, p 1307 (2020)
The ever-increasing functional density and complexity of the satellite systems, the harsh space flight environment, as well as the cost reduction measures that require less operator involvement are increasingly driving the need to develop new approac
Externí odkaz:
https://doaj.org/article/3684df597c314dbfbeff1d9d18fccff2
Publikováno v:
Symmetry, Vol 11, Iss 9, p 1156 (2019)
Position error-compensation control in the servo system of computerized numerical control (CNC) machine tools relies on accurate prediction of dynamic tracking errors of the machine tool feed system. In this paper, in order to accurately predict dyna
Externí odkaz:
https://doaj.org/article/fd6530fd87c24a51bbffa8b2bd6c8ba8
Publikováno v:
Applied Sciences; Volume 13; Issue 12; Pages: 6973
The artificial potential field method is a highly popular obstacle avoidance algorithm which is widely used in the field of industrial robotics due to its high efficiency. However, the traditional artificial potential field method has poor real-time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::21aaff266866a54e4408f48327a0a06f