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.

Study on the network delay of periodic information in the NCS based on EPA

The network delay of the periodic messages transmission in the network control system （NCS） based on Ethemet for plant automation （EPA） is analyzed from the theoretical and experimental perspective in this paper. The composition and the characteristics of the network delay of EPA periodic messages transmission in a subnet is studied through analyzing the information transmission regularity and EPA deterministic scheduling mechanism. On this basis, the queuing delay at communication schedule management entity （EPA _ CSME） that is the most important component of network delay is analyzed, during which the formulas for the queuing delay of periodic messages and other real time parameters are proposed. Furthermore, an experiment is developed to test each component of network delay of periodic messages transmission in a EPA subnet. According to the experimental and the theoretical analysis, the conclusion is drawn that the delay during which the periodic messages wait for the periodic messages transmission time slice is the main factor that causes considerable network delay, and improvement method is presented.

Design and performance analysis of networked control systems with random delay

The design and performance analysis of networked control systems with random network delay in the forward channel is proposed, which are described in a state-space form. A new control scheme is used to overcome the effects of network transmission delay, which is termed networked predictive control （NPC）. Furthermore, three different ways to choose control input are discussed and the performances are analyzed, respectively. Both real-time simulations and practical experiments show the effectiveness of the control scheme.

Fractional delay compensated discrete-time SMC for networked control system

Time-varying network induced delay in the communication channel severely affects the performance of closed loop network control systems. In this paper, a novel idea of compensating the fractional time varying communication delay in the sliding Surface is presented. The fractional time delay in the sensor to controller and controller to actuator channel is approximated using the Thiran approximation technique to design the sliding surface. A discrete-time sliding mode control law is derived using the proposed surface that compensates fractional time delay in sensor to controller and controller to actuator channels for uncertain network control systems. The sufficient condition for closed loop stability of the system is derived using the Lyapunov function. The efficacy of the proposed strategy is supported by the simulation results.

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.

Adaptive clustering hierarchy routing for delay tolerant network

Adaptive clustering hierarchy routing(ACHR) establishes a clusters-based hierarchical hybrid routing algorithm with two-hop local visibility for delay tolerant network(DTN).The major contribution of ACHR is the combination of single copy scheme and multi-copy scheme and the combination of hop-by-hop and multi-hop mechanism ACHR,which has the advantages in simplicity,availability and well-expansibility.The result shows that it can take advantage of the random communication opportunities and local network connectivity,and achieves 1.6 times delivery ratio and 60% overhead compared with its counterpart.

Stability of discrete Hopfield neural networks with delay

Discrete Hopfield neural network with delay is an extension of discrete Hopfield neural network. As it is well known, the stability of neural networks is not only the most basic and important problem but also foundation of the network＇s applications. The stability of discrete HJopfield neural networks with delay is mainly investigated by using Lyapunov function. The sufficient conditions for the networks with delay converging towards a limit cycle of length 4 are obtained. Also, some sufficient criteria are given to ensure the networks having neither a stable state nor a limit cycle with length 2. The obtained results here generalize the previous results on stability of discrete Hopfield neural network with delay and without delay.

Global exponential stability for delayed cellular neural networks and estimate of exponential convergence rate

Some sufficient conditions for the global exponential stability and lower bounds on the rate of exponential convergence of the cellular neural networks with delay (DCNNs) are obtained by means of a method based on delay differential inequality. The method, which does not make use of any Lyapunov functional, is simple and valid for the stability analysis of neural networks with delay. Some previously established results in this paper are shown to be special casses of the presented result.

Global synchronization of general delayed complex networks with stochastic disturbances

In this paper, global synchronization of general delayed complex networks with stochastic disturbances, which is a zero-mean real scalar Wiener process, is investigated. The networks under consideration are continuous-time networks with time-varying delay. Based on the stochastic Lyapunov stability theory, Ito＇s differential rule and the linear matrix inequality （LMI） optimization technique, several delay-dependent synchronous criteria are established, which guarantee the asymptotical mean-square synchronization of drive networks and response networks with stochastic disturbances. The criteria are expressed in terms of LMI, which can be easily solved using the Matlab LMI Control Toolbox. Finally, two examples show the effectiveness and feasibility of the proposed synchronous conditions.

Delay optimization for planar wireless sensor network with N-policy

In N-policy, the nodes attempt to seize the channel when the number of packets in the buffer approaches N. The performance of N-policy on the energy efficiency is widely studied in the past years. And it is presented that there exists one optimal N to minimize the energy consumption. However, it is noticed that the delay raised by N-policy receives little attention. This work mathematically proves the delay to monotonically increase with increasing N in the collision-unfree channel. For planar network where the near-to-sink nodes burden heavier traffic than the external ones, the data stemming from the latter undergo longer delay.The various-N algorithm is proposed to address this phenomenon by decreasing the threshold N of outer nodes. Without the impacting on the network longevity, the maximum delay among the network has decreased 62.9% by the algorithm. Extensive simulations are given to verify the effectiveness and correctness of our analysis.

Delay-Based User Association in Heterogeneous Networks with Backhaul

The Internet of things(IoT) as an important application of future communication networks puts a high premium on delay issues. Thus when Io T applications meet heterogeneous networks(HetNets) where macro cells are overlaid with small cells, some traditional problems need rethinking. In this paper, we investigate the delay-addressed association problem in two-tier Het Nets considering different backhaul technologies. Specifically, millimeter wave and fiber links are used to provide high-capacity backhaul for small cells. We first formulate the user association problem to minimize the total delay which depends on the probability of successful transmission, the number of user terminals(UTs), and the number of base stations(BSs). And then two algorithms for active mode and mixed mode are proposed to minimize the network delay. Simulation results show that algorithms based on mutual selection between UTs and BSs have better performance than those based on distance. And algorithms for mixed modes have less delay than those for active mode when the number of BSs is large enough, compared to the number of UTs.

On Minimizing Delay with Probabilistic Splitting of Traffic Flow in Heterogeneous Wireless Networks

In the paper,we propose a framework to investigate how to effectively perform traffic flow splitting in heterogeneous wireless networks from a queue point.The average packet delay in heterogeneous wireless networks is derived in a probabilistic manner.The basic idea can be understood via treating the integrated heterogeneous wireless networks as different coupled and parallel queuing systems.The integrated network performance can approach that of one queue with maximal the multiplexing gain.For the purpose of illustrating the effectively of our proposed model,the Cellular/WLAN interworking is exploited.To minimize the average delay,a heuristic search algorithm is used to get the optimal probability of splitting traffic flow.Further,a Markov process is applied to evaluate the performance of the proposed scheme and compare with that of selecting the best network to access in terms of packet mean delay and blocking probability.Numerical results illustrate our proposed framework is effective and the flow splitting transmission can obtain more performance gain in heterogeneous wireless networks.

Generalized LMI-based approach to global asymptotic stability of cellular neural networks with delay

A global asymptotic stability problem of cellular neural networks with delay is investigated. A new stability condition is presented based on the Lyapunov-Krasovskii method, which is dependent on the amount of delay. A result is given in the form of a linear matrix inequality, and the admitted upper bound of the delay can be easily obtained. The time delay dependent and independent results can be obtained, which include some previously published results. A numerical example is given to show the effectiveness of the main results.

Global Exponential Stability of Almost Periodic Solution of Cellular Neural Networks with Time-Varying Delays

In this paper, global exponential stability of almost periodic solution of cellular neural networks with time-varing delays （CNNVDs） is considered. By using the methods of the topological degree theory and generalized Halanay inequality, a few new applicable criteria are established for the existence and global exponential stability of almost periodic solution. Some previous results are improved and extended in this letter and one example is given to illustrate the effectiveness of the new results.

Cache-Assign-Forward Architecture for Efficient Communication in Hybrid Delay-Tolerant Networks

Delay-Tolerant Networks (DTNs) are wireless networks that often experience temporary, even long-duration partitioning. Current DTN researches mainly focus on pure delay-tolerant networks that are extreme environments within a limited application scope. It motivates the identification of a more reasonable and valuable DTN architecture, which can be applied in a wider range of environments to achieve interoperability between some networks suffering from frequent network partitioning, and other networks provided with stable and high speed Internet access. Such hybrid delay-tolerant networks have a lot of applications in real world. A novel and practical Cache-Assign-Forward (CAF) architecture is proposed as an appropriate approach to tie together such hybrid networks to achieve an efficient and flexible data communication. Based on CAF, we enhance the existing DTN routing protocols and apply them to complex hybrid delay-tolerant networks. Simulations show that CAF can improve DTN routing performance significantly in hybrid DTN environments.

Global impulsive exponential synchronization of stochastic perturbed chaotic delayed neural networks

In this paper, the global impulsive exponential synchronization problem of a class of chaotic delayed neural networks （DNNs） with stochastic perturbation is studied. Based on the Lyapunov stability theory, stochastic analysis approach and an efficient impulsive delay differential inequality, some new exponential synchronization criteria expressed in the form of the linear matrix inequality （LMI） are derived. The designed impulsive controller not only can globally exponentially stabilize the error dynamics in mean square, but also can control the exponential synchronization rate. Furthermore, to estimate the stable region of the synchronization error dynamics, a novel optimization control al- gorithm is proposed, which can deal with the minimum problem with two nonlinear terms coexisting in LMIs effectively. Simulation results finally demonstrate the effectiveness of the proposed method.

Nonlinear H_∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays

This paper is concerned with the problem of robust H∞ control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays. A sufficient condition is presented for the existence of H∞ control based on the Lyapunov stability theory. The stability criterion is described in terms of linear matrix inequalities （LMIs）, which can be easily checked in practice. An example is provided to demonstrate the effectiveness of the proposed result.

Effects of information transmission delay and channel blocking on synchronization in scale-free Hodgkin-Huxley neuronal networks

In this paper,we investigate the evolution of spatiotemporal patterns and synchronization transitions in dependence on the information transmission delay and ion channel blocking in scale-free neuronal networks.As the underlying model of neuronal dynamics,we use the Hodgkin-Huxley equations incorporating channel blocking and intrinsic noise.It is shown that delays play a significant yet subtle role in shaping the dynamics of neuronal networks.In particular,regions of irregular and regular propagating excitatory fronts related to the synchronization transitions appear intermittently as the delay increases.Moreover,the fraction of working sodium and potassium ion channels can also have a significant impact on the spatiotemporal dynamics of neuronal networks.As the fraction of blocked sodium channels increases,the frequency of excitatory events decreases,which in turn manifests as an increase in the neuronal synchrony that,however,is dysfunctional due to the virtual absence of large-amplitude excitations.Expectedly,we also show that larger coupling strengths improve synchronization irrespective of the information transmission delay and channel blocking.The presented results are also robust against the variation of the network size,thus providing insights that could facilitate understanding of the joint impact of ion channel blocking and information transmission delay on the spatiotemporal dynamics of neuronal networks.

Stability for Cellular Neural Networks with Delay

The cellular neural networks with delay (DCNN’s) are investigated, and some new sufficient conditions on asymptotical stability of DCNN’s are derived by constructing the Liapunov functional and utilizing M ? matrixand theω?limit set. It is shown that the new conditions are not related to the delayed parameter.