Exponential stability criteria on neural networks with continuously distributed delays

The exponential stability of a class of neural networks with continuously distributed delays is investigated by employing a novel Lyapunov-Krasovskii functional. Through introducing some free-weighting matrices and the equivalent descriptor form, a delay-dependent stability criterion is established for the addressed systems. The condition is expressed in terms of a linear matrix inequality （LMI）, and it can be checked by resorting to the LMI in the Matlab toolbox. In addition, the proposed stability criteria do not require the monotonicity of the activation functions and the derivative of a time-varying delay being less than 1, which generalize and improve earlier methods. Finally, numerical examples are given to show the effectiveness of the obtained methods.

NEURAL NETWORK SMITH PREDICTIVE CONTROL FOR TELEROBOTS WITH TIME DELAY

A neural network Smith predictive control strategy is proposed to deal with inpu t and feedback time delays in telerobot systems. The delay time is assumed to b e invariant and unknown. The proposed control structure consists of a slave syst em and a master controller. In the slave system, a recurrent neural network (RNN ) with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant, which is used to linearize the slave s ystem. The master controller is a Smith predictor for the linearized slave syste m, which provides prediction and maintains the desirable tracking performance. S tability propriety is guaranteed based on the Lyapunov method. A simulation of a two-link robotic manipulator is provided to illustrate the effectiveness of th e proposed control strategy.

Exponential stability and existence of periodic solutions for a class of recurrent neural networks with delays

Both the global exponential stability and the existence of periodic solutions for a class of recurrent neural networks with continuously distributed delays （RNNs） are studied. By employing the inequality α∏k=1^m bk^qk≤1/r ∑qkbk^r＋1/rα^r（α≥0,bk≥0,qk〉0,with ∑k=1^m qk=r-1,r≥1, constructing suitable Lyapunov r k=l k=l functions and applying the homeomorphism theory, a family of simple and new sufficient conditions are given ensuring the global exponential stability and the existence of periodic solutions of RNNs. The results extend and improve the results of earlier publications.

Improved results on synchronization in arrays of coupled delayed neural networks with hybrid coupling

In order to investigate the influence of hybrid coupling on the synchronization of delayed neural networks, by choosing an improved delay-dependent Lyapunov-Krasovskii functional, one less conservative asymptotical criterion based on linear matrix inequality （LMI） is established. The Kronecker product and convex combination techniques are employed. Also the bounds of time-varying delays and delay derivatives are fully considered. By adjusting the inner coupling matrix parameters and using the Matlab LMI toolbox, the design and applications of addressed coupled networks can be realized. Finally, the efficiency and applicability of the proposed results are illustrated by a numerical example with simulations.

Time-stamped predictive functional control for networked control systems with random delays

The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is proposed,which generalizes the standard PFC algorithm to networked control systems with random delays.The algorithm uses the time-stamp method to estimate the control delay,predicts the future outputs based on a discrete time delay state space model,and drives the control law that applies to an NCS from the idea of a PFC algorithm.A networked control system was constructed based on TrueTime simulator,with which the time-stamped PFC algorithm was compared with the standard PFC algorithm.The response curves show that the proposed algorithm has better control performance.

A simulation model for estimating train and passenger delays in large-scale rail transit networks

A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that the time varying original-destination demand and passenger path choice probability were given. Passengers were assumed not to change their destinations and travel paths after delay occurs. CapaciW constraints of train and queue rules of alighting and boarding were taken into account. By using the time-driven simulation, the states of passengers, trains and other facilities in the network were updated every time step. The proposed methodology was also tested in a real network, for demonstration. The results reveal that short train delay does not necessarily result in passenger delays, while, on the contrary, some passengers may get benefits from the short delay. However, large initial train delay may result in not only knock-on train and passenger delays along the same line, but also the passenger delays across the entire rail transit network.

Adaptive output feedback control for nonlinear time-delay systems using neural network

This paper extends the adaptive neural network （NN） control approaches to a class of unknown output feedback nonlinear time-delay systems. An adaptive output feedback NN tracking controller is designed by backstepping technique. NNs are used to approximate unknown functions dependent on time delay, Delay-dependent filters are introduced for state estimation. The domination method is used to deal with the smooth time-delay basis functions. The adaptive bounding technique is employed to estimate the upper bound of the NN approximation errors. Based on Lyapunov- Krasovskii functional, the semi-global uniform ultimate boundedness of all the signals in the closed-loop system is proved, The feasibility is investigated by two illustrative simulation examples.

Improved H_∞ control for networked control systems with network-induced delay and packet dropout

The H_∞ performance analysis and controller design for linear networked control systems(NCSs) are presented.The NCSs are considered a linear continuous system with time-varying interval input delay by assuming that the sensor is time-driven and the logic Zero-order-holder(ZOH) and controller are event-driven.Based on this model,the delay interval is divided into two equal subintervals for H_∞ performance analysis.An improved H_∞ stabilization condition is obtained in linear matrix inequalities(LMIs) framework by adequately considering the information about the bounds of the input delay to construct novel Lyapunov–Krasovskii functionals(LKFs).For the purpose of reducing the conservatism of the proposed results,the bounds of the LKFs differential cross terms are properly estimated without introducing any slack matrix variables.Moreover,the H_∞ controller is reasonably designed to guarantee the robust asymptotic stability for the linear NCSs with an H_∞ performance level γ.Numerical simulation examples are included to validate the reduced conservatism and effectiveness of our proposed method.

Analysis of cumulative handoff delay for graded secondary users in cognitive radio networks

According to the fact that the secondary users＇ delay requirements for data transmission are not unitary in cognitive radio networks, the secondary users are divided into two classes, denoted by SU1 and SU2, respectively. It is assumed that SU1 has a higher priority to occupy the primary users＇ unutilized channels than SU2. A preemptive resume priority M/G/1 queuing network is used to model the multiple spectrum handoffs processing. By using a state transition probability matrix and a cost matrix, the average cumulative delays of SU1 and SU2 are calculated, respectively. Numerical results show that the more the primary user＇s traffic load, the more rapidly the SU2＇s cumulative handoff delay grows. Compared with the networks where secondary users are unitary, the lower the SUI＇s arrival rate, the more obviously both SUI＇s and SU2＇s handoff delays decrease. The admission access regions limited by the maximum tolerable delay can also facilitate the design of admission control rules for graded secondary users.

A Spatial-Temporal Network Perspective for the Propagation Dynamics of Air Traffic Delays

Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magnified and propagated throughout these systems,resulting in the emergent behavior known as delay propagation.An understanding of delay propagation dynamics is pertinent to modern air traffic management.In this work,we present a complex network perspective of delay propagation dynamics.Specifically,we model air traffic scenarios using spatial–temporal networks with airports as the nodes.To establish the dynamic edges between the nodes,we develop a delay propagation method and apply it to a given set of air traffic schedules.Based on the constructed spatial-temporal networks,we suggest three metrics-magnitude,severity,and speed-to gauge delay propagation dynamics.To validate the effectiveness of the proposed method,we carry out case studies on domestic flights in the Southeastern Asia region(SAR)and the United States.Experiments demonstrate that the propagation magnitude in terms of the number of flights affected by delay propagation and the amount of propagated delays for the US traffic are respectively five and ten times those of the SAR.Experiments further reveal that the propagation speed for US traffic is eight times faster than that of the SAR.The delay propagation dynamics reveal that about six hub airports in the SAR have significant propagated delays,while the situation in the United States is considerably worse,with a corresponding number of around 16.This work provides a potent tool for tracing the evolution of air traffic delays.

Real-time multi-step prediction control for BP network with delay

Real time multi step prediction of BP network based on dynamical compensation of system characteristics is suggested by introducing the first and second derivatives of the system and network outputs into the network input layer, and real time multi step prediction control is proposed for the BP network with delay on the basis of the results of real time multi step prediction, to achieve the simulation of real time fuzzy control of the delayed time system.

Analysis of PROFIBUS-DP Network Delay and Its Influence on the Performance of Control Systems

This paper analyzes PROFIBUS-DP network delay in detail and presents the calculational formula of its maximum time-delay, which is significant to the research of PROFIBUS-DP. At the same time, the paper puts forward a method of simplifying the network induced time-varying indeterminate system according to the features of the network. Through the analysis of a pump-control-motor system which is composed of PROFIBUS-DP network, it illustrates the network＇s influence on the performance of control systems. This method helps to design and analyze the network＇s influence on the performance of control systems, which is of considerable practical value in a time when network control systern is widely used.

Research on Network Delays of Networked Control Systems

In networked control systems (NCS), the main problem is time delays induced by communication network, which can deteriorate the performance of the systems, even cause the systems instability. If we know the exact network delays, we can compensate for their effect by modifying the parameters of the controller. Hence how to get the knowledge of these delays in the network is critical. This paper analyzed the different characteristics of network delays from sensor to controller and from controller to actuator and presented the methods of online evaluation of these delays. The experiment shows these methods are valid.

Decoupled Delay and Bandwidth Centralized Queue-Based QoS Scheme in OpenFlow Networks

There are an increasing of scenarios that require the independent bandwidth and delay demands. For instance, in a data center, the interactive message would not occupy much bandwidth, but it requires the rigorous demands for the delay. However, the existing QoS approaches are mainly bandwidth based, which are inappropriate for these scenarios. Hence, we propose the decoupled scheme in the OpenFlow networks to provide the centralized differential bandwidth and delay control. We leverage the mature HTB to manage the bandwidth. And we design the Queue Delay Management Scheme (QDMS) for queuing delay arrangement, as well as the Comprehensive Parameters based Dijkstra Route algorithm (CPDR) for the propagation delay control. The evaluation results verify the decoupling effectiveness. And the decoupled scheme can reduce the delay for high priority flows.

LanePost:Lane-Based Optimal Routing Protocol for Delay-Tolerant Maritime Networks

Ship.to.ship, ship.to.shore radio links empowered by Wi Fi, Wi MAX etc have been recently exploited to build maritime multi.hop mesh networks to provide internet services to on.ship users. However, because of the mobility of the vessels/ships and the large inter.ship distances, nodes in the maritime network are frequently disconnected, forcing data communication in the maritime mesh networks to be opportunistic and delay.tolerant. In this paper, we present Lane Post, an optimization approach for maritime delay.tolerant routing protocol. We exploit the shipping lane information to predict the rendezvous opportunities of the ships to optimize the route selection in delay.tolerant routing. In particular, we show that when the shipping lane information is available, an opportunistic routing graph(ORG) for each ship can be constructed to predict its multi.hop data routing opportunities to the other ships or to the shore. Based on the ORG, we develop an optimal route protocol(i.e., Lane Post) for each ship to minimize its delay of multi.hop packet delivery via dynamic programming. We discussed the ways of collecting shipping lane information by centralized method or distributed method.The proposed Lane Post protocol was evaluated by ONE, an open.source delay.tolerant network simulator, which shows its dramatic performance improvement in terms of delay reduction compared to the state.of.the.art opportunistic routing protocols.

Uniformed model of networked control systems with long time delay

Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems （NCS）. The defining feature of an NCS is that information is exchanged using a network among control system components. Two new concepts including long time delay and short time delay are proposed. The sensor is almost always clock driven. The controller or the actuator is either clock driven or event driven. Four possible driving modes of networked control systems are presented. The open loop mathematic models of networked control systems with long time delay are developed when the system is driven by anyone of the four different modes. The uniformed modeling method of networked control systems with long time delay is proposed. The simulation results are given in the end.

ADAPTIVE PINNING SYNCHRONIZATION OF COUPLED NEURAL NETWORKS WITH MIXED DELAYS AND VECTOR-FORM STOCHASTIC PERTURBATIONS

In this article, we consider the global chaotic synchronization of general cou- pled neural networks, in which subsystems have both discrete and distributed delays. Stochastic perturbations between subsystems are also considered. On the basis of two sim- ple adaptive pinning feedback control schemes, Lyapunov functional method, and stochas- tic analysis approach, several sufficient conditions are developed to guarantee global syn- chronization of the coupled neural networks with two kinds of delay couplings, even if only partial states of the nodes are coupled. The outer-coupling matrices may be symmetric or asymmetric. Unlike existing results that an isolate node is introduced as the pinning target, we pin to help the network realizing synchronization without introducing any iso- late node when the network is not synchronized. As a by product, sufficient conditions under which the network realizes synchronization without control are derived. Numerical simulations confirm the effectiveness of the obtained results.

Taming desynchronized bursting with delays in the Macaque cortical network

Inhibitory coupled bursting Hindmarsh-Rose neurons are considered as constitutive units of the Macaque corti- cal network. In the absence of information transmission delay the bursting activity is desynchronized, giving rise to spatiotemporally disordered dynamics. This paper shows that the introduction of finite delays can lead to the synchro- nization of bursting and thus to the emergence of coherent propagating fronts of excitation in the space-time domain. Moreover, it shows that the type of synchronous bursting is uniquely determined by the delay length, with the transi- tions from one type to the other occurring in a step-like manner depending on the delay. Interestingly, as the delay is tuned close to the transition points, the synchronization deteriorates, which implies the coexistence of different bursting attractors. These phenomena can be observed by different but fixed coupling strengths, thus indicating a new role for information transmission delays in realistic neuronal networks.

STABILITY OF A CLASS OF NEURAL NETWORK MODELS WITH DELAY

In this paper, by using Liapunov functional, some sufficient conditions are obtained for the stability of the equilibrium of a neural network model with delay of the type u ′ i(t)=-b iu i(t)+∑nj=1T ij f j(μ ju j(t-τ j))+c i, τ j≥0, i=1,2,…,n.

Global exponential stability of Cohen-Grossberg neural networks with variable delays

A class of generalized Cohen-Grossberg neural networks（CGNNs） with variable de- lays are investigated. By introducing a new type of Lyapunov functional and applying the homeomorphism theory and inequality technique, some new conditions axe derived ensuring the existence and uniqueness of the equilibrium point and its global exponential stability for CGNNs. These results obtained are independent of delays, develop the existent outcome in the earlier literature and are very easily checked in practice.