Documents disponibles écrits par cet auteur

An experimental study of the laminar flow separation on a low-Reynolds-number airfoil / Hui, Hu in Transactions of the ASME . Journal of fluids engineering, Vol. 130 N° 5 (Mai 2008) 

Public ISBD [article]  in Transactions of the ASME . Journal of fluids engineering > Vol. 130 N° 5 (Mai 2008) . - 11 p. Titre : An experimental study of the laminar flow separation on a low-Reynolds-number airfoil Type de document : texte imprimé Auteurs : Hui, Hu, Auteur ; Zifeng Yang, Auteur Année de publication : 2009 Article en page(s) : 11 p. Note générale : Fluids engineering Langues : Anglais (eng) Mots-clés : Separation  (technology);  airfoils;  bubbles;  pressure;  boundary  layers;  laminar  flow;  flow  (dynamics);  drag  (fluid  dynamics) Résumé : An experimental study was conducted to characterize the transient behavior of laminar flow separation on a NASA low-speed GA (W)-1 airfoil at the chord Reynolds number of 70,000. In addition to measuring the surface pressure distribution around the airfoil, a high-resolution particle image velocimetry (PIV) system was used to make detailed flow field measurements to quantify the evolution of unsteady flow structures around the airfoil at various angles of attack (AOAs). The surface pressure and PIV measurements clearly revealed that the laminar boundary layer would separate from the airfoil surface, as the adverse pressure gradient over the airfoil upper surface became severe at AOA≥8.0deg. The separated laminar boundary layer was found to rapidly transit to turbulence by generating unsteady Kelvin–Helmholtz vortex structures. After turbulence transition, the separated boundary layer was found to reattach to the airfoil surface as a turbulent boundary layer when the adverse pressure gradient was adequate at AOA<12.0deg, resulting in the formation of a laminar separation bubble on the airfoil. The turbulence transition process of the separated laminar boundary layer was found to be accompanied by a significant increase of Reynolds stress in the flow field. The reattached turbulent boundary layer was much more energetic, thus more capable of advancing against an adverse pressure gradient without flow separation, compared to the laminar boundary layer upstream of the laminar separation bubble. The laminar separation bubble formed on the airfoil upper surface was found to move upstream, approaching the airfoil leading edge as the AOA increased. While the total length of the laminar separation bubble was found to be almost unchanged (∼20% of the airfoil chord length), the laminar portion of the separation bubble was found to be slightly stretched, and the turbulent portion became slightly shorter with the increasing AOA. After the formation of the separation bubble on the airfoil, the increase rate of the airfoil lift coefficient was found to considerably degrade, and the airfoil drag coefficient increased much faster with increasing AOA. The separation bubble was found to burst suddenly, causing airfoil stall, when the adverse pressure gradient became too significant at AOA>12.0deg. En ligne : http://fluidsengineering.asmedigitalcollection.asme.org/issue.aspx?journalid=122 [...] [article] An experimental study of the laminar flow separation on a low-Reynolds-number airfoil [texte imprimé] / Hui, Hu, Auteur ; Zifeng Yang, Auteur . - 2009 . - 11 p. Fluids engineering Langues : Anglais (eng) in Transactions of the ASME . Journal of fluids engineering > Vol. 130 N° 5 (Mai 2008) . - 11 p. Mots-clés : Separation  (technology);  airfoils;  bubbles;  pressure;  boundary  layers;  laminar  flow;  flow  (dynamics);  drag  (fluid  dynamics) Résumé : An experimental study was conducted to characterize the transient behavior of laminar flow separation on a NASA low-speed GA (W)-1 airfoil at the chord Reynolds number of 70,000. In addition to measuring the surface pressure distribution around the airfoil, a high-resolution particle image velocimetry (PIV) system was used to make detailed flow field measurements to quantify the evolution of unsteady flow structures around the airfoil at various angles of attack (AOAs). The surface pressure and PIV measurements clearly revealed that the laminar boundary layer would separate from the airfoil surface, as the adverse pressure gradient over the airfoil upper surface became severe at AOA≥8.0deg. The separated laminar boundary layer was found to rapidly transit to turbulence by generating unsteady Kelvin–Helmholtz vortex structures. After turbulence transition, the separated boundary layer was found to reattach to the airfoil surface as a turbulent boundary layer when the adverse pressure gradient was adequate at AOA<12.0deg, resulting in the formation of a laminar separation bubble on the airfoil. The turbulence transition process of the separated laminar boundary layer was found to be accompanied by a significant increase of Reynolds stress in the flow field. The reattached turbulent boundary layer was much more energetic, thus more capable of advancing against an adverse pressure gradient without flow separation, compared to the laminar boundary layer upstream of the laminar separation bubble. The laminar separation bubble formed on the airfoil upper surface was found to move upstream, approaching the airfoil leading edge as the AOA increased. While the total length of the laminar separation bubble was found to be almost unchanged (∼20% of the airfoil chord length), the laminar portion of the separation bubble was found to be slightly stretched, and the turbulent portion became slightly shorter with the increasing AOA. After the formation of the separation bubble on the airfoil, the increase rate of the airfoil lift coefficient was found to considerably degrade, and the airfoil drag coefficient increased much faster with increasing AOA. The separation bubble was found to burst suddenly, causing airfoil stall, when the adverse pressure gradient became too significant at AOA>12.0deg. En ligne : http://fluidsengineering.asmedigitalcollection.asme.org/issue.aspx?journalid=122 [...]

Fuzzy Supervisory Sliding-Mode and Neural-Network Control for Robotic Manipulators / Hui, Hu in IEEE transactions on industrial electronics, Vol. 53 N° 3 (Juin 2006)

Public ISBD [article]  in IEEE transactions on industrial electronics > Vol. 53 N° 3 (Juin 2006) . - 929- 940 p. Titre : Fuzzy Supervisory Sliding-Mode and Neural-Network Control for Robotic Manipulators Titre original : Commande de Mode Coulissant de Surveillance Brouillé et de Réseau Neurologique pour les Robots Manipulateurs Type de document : texte imprimé Auteurs : Hui, Hu, Auteur ; Woo, Peng-Yung, Auteur Article en page(s) : 929- 940 p. Note générale : Génie Electrique Langues : Anglais (eng) Mots-clés : Fuzzy  supervisory  control  Fuzzy  supervisory  sliding-mode  and  neural-network  control  Neural-network  control  Robotic  control  Sliding-mode  control.Commande  de  surveillance  brouillée  Commande  de  mode  coulissant  de  surveillance  brouillé  et  de  réseau  neurologique  Commande  de  réseau  neurologique  Commande  robotique  Commande  de  mode  de  glissement. Index. décimale : 621 Ingénierie mécanique en général. Technologie nucléaire. Ingénierie électrique. Machinerie Résumé : Highly nonlinear, highly coupled, and time-varying robotic manipulators suffer from structured and unstructured uncertainties. Sliding-mode control (SMC) is effective in overcoming uncertainties and has a fast transient response, while the control effort is discontinuous and creates chattering. The neural network has an inherent ability to learn and approximate a nonlinear function to arbitrary accuracy, which is used in the controllers to model complex processes and compensate for unstructured uncertainties. However, the unavoidable learning procedure degrades its transient performance in the presence of disturbance. A novel approach is presented to overcome their demerits and take advantage of their attractive features of robust and intelligent control. The proposed control scheme combines the SMC and the neural-network control (NNC) with different weights, which are determined by a fuzzy supervisory controller. This novel scheme is named fuzzy supervisory sliding-mode and neural-network control (FSSNC). The convergence and stability of the proposed control system are proved by using Lyapunov's direct method. Simulations for different situations demonstrate its robustness with satisfactory performance. Fortement non-linéaire, fortement couplé, et le temps changeant les robots manipulateurs souffrent des incertitudes structurées et non structurées. En glissant le mode commander (SMC) est efficace en surmontant des incertitudes et a une réponse passagère rapide, alors que l'effort de commande est discontinu et crée la vibration. Le réseau neurologique a une capacité inhérente d'apprendre et approcher une fonction non-linéaire de l'exactitude arbitraire, qui est employée dans les contrôleurs pour modeler des processus complexes et pour compenser des incertitudes non structurées. Cependant, le procédé de étude inévitable dégrade son exécution passagère en présence de la perturbation. Une approche de roman est présentée pour surmonter leurs démérites et pour tirer profit de leurs dispositifs attrayants de commande robuste et intelligente. L'arrangement proposé de commande combine le SMC et la commande de neural-réseau (NNC) avec différents poids, qui sont déterminés par un contrôleur de surveillance brouillé. Cet arrangement de roman est appelé la commande de mode coulissant de surveillance brouillé et de réseau neurologique (FSSNC). La convergence et la stabilité du système de commande proposé sont prouvées en employant la méthode directe de Lyapunov. Les simulations pour différentes situations démontrent sa robustesse avec l'exécution satisfaisante. DEWEY : 621 ISSN : 0278-0046 [article] Fuzzy Supervisory Sliding-Mode and Neural-Network Control for Robotic Manipulators = Commande de Mode Coulissant de Surveillance Brouillé et de Réseau Neurologique pour les Robots Manipulateurs [texte imprimé] / Hui, Hu, Auteur ; Woo, Peng-Yung, Auteur . - 929- 940 p. Génie Electrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 53 N° 3 (Juin 2006) . - 929- 940 p. Mots-clés : Fuzzy  supervisory  control  Fuzzy  supervisory  sliding-mode  and  neural-network  control  Neural-network  control  Robotic  control  Sliding-mode  control.Commande  de  surveillance  brouillée  Commande  de  mode  coulissant  de  surveillance  brouillé  et  de  réseau  neurologique  Commande  de  réseau  neurologique  Commande  robotique  Commande  de  mode  de  glissement. Index. décimale : 621 Ingénierie mécanique en général. Technologie nucléaire. Ingénierie électrique. Machinerie Résumé : Highly nonlinear, highly coupled, and time-varying robotic manipulators suffer from structured and unstructured uncertainties. Sliding-mode control (SMC) is effective in overcoming uncertainties and has a fast transient response, while the control effort is discontinuous and creates chattering. The neural network has an inherent ability to learn and approximate a nonlinear function to arbitrary accuracy, which is used in the controllers to model complex processes and compensate for unstructured uncertainties. However, the unavoidable learning procedure degrades its transient performance in the presence of disturbance. A novel approach is presented to overcome their demerits and take advantage of their attractive features of robust and intelligent control. The proposed control scheme combines the SMC and the neural-network control (NNC) with different weights, which are determined by a fuzzy supervisory controller. This novel scheme is named fuzzy supervisory sliding-mode and neural-network control (FSSNC). The convergence and stability of the proposed control system are proved by using Lyapunov's direct method. Simulations for different situations demonstrate its robustness with satisfactory performance. Fortement non-linéaire, fortement couplé, et le temps changeant les robots manipulateurs souffrent des incertitudes structurées et non structurées. En glissant le mode commander (SMC) est efficace en surmontant des incertitudes et a une réponse passagère rapide, alors que l'effort de commande est discontinu et crée la vibration. Le réseau neurologique a une capacité inhérente d'apprendre et approcher une fonction non-linéaire de l'exactitude arbitraire, qui est employée dans les contrôleurs pour modeler des processus complexes et pour compenser des incertitudes non structurées. Cependant, le procédé de étude inévitable dégrade son exécution passagère en présence de la perturbation. Une approche de roman est présentée pour surmonter leurs démérites et pour tirer profit de leurs dispositifs attrayants de commande robuste et intelligente. L'arrangement proposé de commande combine le SMC et la commande de neural-réseau (NNC) avec différents poids, qui sont déterminés par un contrôleur de surveillance brouillé. Cet arrangement de roman est appelé la commande de mode coulissant de surveillance brouillé et de réseau neurologique (FSSNC). La convergence et la stabilité du système de commande proposé sont prouvées en employant la méthode directe de Lyapunov. Les simulations pour différentes situations démontrent sa robustesse avec l'exécution satisfaisante. DEWEY : 621 ISSN : 0278-0046