A networked control and supervision system （NCSS） based on LonWorks fieldbus and lntranet/Intemet was designed, which was composed of the universal intelligent control nodes （ICNs）, the visual control and supervis...A networked control and supervision system （NCSS） based on LonWorks fieldbus and lntranet/Intemet was designed, which was composed of the universal intelligent control nodes （ICNs）, the visual control and supervision configuration platforms （VCCP and VSCP） and an Intranet/Internet-based remote supervision platform （RSP）. The ICNs were connected to field devices, such as sensors, actuators and controllers. The VCCP and VSCP were implemented by means of a graphical programming environment and network management so as to simplify the tasks of programming and maintaining the ICNs. The RSP was employed to perform the remote supervision function, which was based on a three-layer browser/server（B/S） structure mode. The validity of the NCSS was demonstrated by laboratory experiments.展开更多
The problem of the stability analysis and controller design which the network-induced delays and data dropout problems network-induced delays are assumed to be time-varying and bounded, for Lurie networked control sys...The problem of the stability analysis and controller design which the network-induced delays and data dropout problems network-induced delays are assumed to be time-varying and bounded, for Lurie networked control systems （NCSs） is investigated, in are simultaneously considered. By considering that the and analyzing the relationship between the delay and its upper bound, employing a Lyapunov-Krasovskii function and an integral inequality approach, an improved stability criterion for NCSs is proposed. Furthermore, the resulting condition is extended to design a less conservative state feedback controller by employing an improved cone complementary linearization （ICCL） algorithm. Numerical examples are provided to show the effectiveness of the method.展开更多
Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a nov...Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a novel method via T-S cloud inference network optimized by genetic algorithm(GA) is proposed. T-S cloud inference network is constructed with T-S fuzzy neural network and the cloud model. So, the rapid of fuzzy logic and the uncertainty of cloud model for processing data are both taken into account. What's more, GA possesses good parallel design structure and global optimization characteristics. Compared with the simulation recognition results of traditional BP Algorithm, GA is more accurate and effective. Moreover, virtual reality technology is introduced into the field of shape control by Lab VIEW, MATLAB mixed programming. And virtual flatness pattern recognition interface is designed.Therefore, the data of engineering analysis and the actual model are combined with each other, and the shape defects could be seen more lively and intuitively.展开更多
基金Project (60425310) supported by the National Natural Science Foundation of ChinaProject(2006AA04Z172) supported by the High-TechResearch and Development Program of China
文摘A networked control and supervision system （NCSS） based on LonWorks fieldbus and lntranet/Intemet was designed, which was composed of the universal intelligent control nodes （ICNs）, the visual control and supervision configuration platforms （VCCP and VSCP） and an Intranet/Internet-based remote supervision platform （RSP）. The ICNs were connected to field devices, such as sensors, actuators and controllers. The VCCP and VSCP were implemented by means of a graphical programming environment and network management so as to simplify the tasks of programming and maintaining the ICNs. The RSP was employed to perform the remote supervision function, which was based on a three-layer browser/server（B/S） structure mode. The validity of the NCSS was demonstrated by laboratory experiments.
基金Project(61025015)supported by the National Natural Science Foundation of China for Distinguished Young ScholarsProject (IRT1044)supported by the Program for Changjiang Scholars and Innovative Research Team in University of China+2 种基金Projects(61143004,61203136,61074067,61273185)supported by the National Natural Science Foundation of ChinaProjects(12JJ4062,11JJ2033)supported by the Natural Science Foundation of Hunan Province,ChinaProject(12C0078)supported by Hunan Provincial Department of Education,China
文摘The problem of the stability analysis and controller design which the network-induced delays and data dropout problems network-induced delays are assumed to be time-varying and bounded, for Lurie networked control systems （NCSs） is investigated, in are simultaneously considered. By considering that the and analyzing the relationship between the delay and its upper bound, employing a Lyapunov-Krasovskii function and an integral inequality approach, an improved stability criterion for NCSs is proposed. Furthermore, the resulting condition is extended to design a less conservative state feedback controller by employing an improved cone complementary linearization （ICCL） algorithm. Numerical examples are provided to show the effectiveness of the method.
基金Project(LJRC013)supported by the University Innovation Team of Hebei Province Leading Talent Cultivation,China
文摘Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a novel method via T-S cloud inference network optimized by genetic algorithm(GA) is proposed. T-S cloud inference network is constructed with T-S fuzzy neural network and the cloud model. So, the rapid of fuzzy logic and the uncertainty of cloud model for processing data are both taken into account. What's more, GA possesses good parallel design structure and global optimization characteristics. Compared with the simulation recognition results of traditional BP Algorithm, GA is more accurate and effective. Moreover, virtual reality technology is introduced into the field of shape control by Lab VIEW, MATLAB mixed programming. And virtual flatness pattern recognition interface is designed.Therefore, the data of engineering analysis and the actual model are combined with each other, and the shape defects could be seen more lively and intuitively.
