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
The assumption widely used in the user equilibrium model for stochastic network was that the probability distributions of the travel time were known explicitly by travelers. However, this distribution may be unavailab...The assumption widely used in the user equilibrium model for stochastic network was that the probability distributions of the travel time were known explicitly by travelers. However, this distribution may be unavailable in reality. By relaxing the restrictive assumption, a robust user equilibrium model based on cumulative prospect theory under distribution-free travel time was presented. In the absence of the cumulative distribution function of the travel time, the exact cumulative prospect value(CPV) for each route cannot be obtained. However, the upper and lower bounds on the CPV can be calculated by probability inequalities.Travelers were assumed to choose the routes with the best worst-case CPVs. The proposed model was formulated as a variational inequality problem and solved via a heuristic solution algorithm. A numerical example was also provided to illustrate the application of the proposed model and the efficiency of the solution algorithm.展开更多
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(2012CB725400)supported by the National Basic Research Program of ChinaProjects(71271023,71322102,7121001)supported by the National Natural Science Foundation of China
文摘The assumption widely used in the user equilibrium model for stochastic network was that the probability distributions of the travel time were known explicitly by travelers. However, this distribution may be unavailable in reality. By relaxing the restrictive assumption, a robust user equilibrium model based on cumulative prospect theory under distribution-free travel time was presented. In the absence of the cumulative distribution function of the travel time, the exact cumulative prospect value(CPV) for each route cannot be obtained. However, the upper and lower bounds on the CPV can be calculated by probability inequalities.Travelers were assumed to choose the routes with the best worst-case CPVs. The proposed model was formulated as a variational inequality problem and solved via a heuristic solution algorithm. A numerical example was also provided to illustrate the application of the proposed model and the efficiency of the solution algorithm.
