HYBRID FILTER WITH PREDICT-ESTIMATOR AND COMPENSATOR FOR THE LINEAR TIME INVARIANT DELAYED SYSTEM

This paper investigates the problem of real-time estimation for one kind of linear time invariant systems which subject to limited communication capacity. The communication limitations include signal transmission delay, the out-of-sequence measurements and data packet dropout, which appear typically in a network environment. The kernel of filter design is equally to formularize the traditional Kalman filter as one linear weighted summation which is composed of the initial state estimate and all sequential sampled measurements. For it can adapt aforementioned information limitations, the linear weighted summation is then decomposed into two stages. One is a predict-estimator composed by all reached measurements, another is one compensator constructed by those time-delayed data. In the network environment, there are obvious differences between the new hybrid filter and those existing delayed Kalman filters. For example, the novel filter can be optimal in the sense of linear minimum mean square error as soon as all measurements available and has the lowest running time than these existing delayed filters. One simulation, including two cases, is utilized to illustrate the design procedures proposed in this paper.

Guaranteed Cost Active Fault-tolerant Control of Networked Control System with Packet Dropout and Transmission Delay

The problem of guaranteed cost active fault-tolerant controller （AFTC） design for networked control systems （NCSs） with both packet dropout and transmission delay is studied in this paper. Considering the packet dropout and transmission delay, a piecewise constant controller is adopted. With a guaranteed cost function, optimal controllers whose number is equal to the number of actuators are designed, and the design process is formulated as a convex optimal problem that can be solved by existing software. The control strategy is proposed as follows： when actuator failures appear, the fault detection and isolation unit sends out the information to the controller choosing strategy, and then the optimal stabilizing controller with the smallest guaranteed cost value is chosen. Two illustrative examples are given to demonstrate the effectiveness of the proposed approach. By comparing with the existing methods, it can be seen that our method has a better performance.

Reducing energy consumption optimization selection of path transmission routing algorithm in opportunistic networks

Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy consumption optimal selection of path transmission(OSPT) routing algorithm in opportunistic networks.This algorithm designs a dynamic random network topology,creates a dynamic link,and realizes an optimized selected path.This algorithm solves a problem that nodes are unable to deliver messages for a long time in opportunistic networks.According to the simulation experiment,OSPT improves deliver ratio,and reduces energy consumption,cache time and transmission delay compared with the Epidemic Algorithm and Spray and Wait Algorithm in opportunistic networks.

Global dynamics behaviors for new delay SEIR epidemic disease model with vertical transmission and pulse vaccination

A robust SEIR epidemic disease model with a profitless delay and vertical transmission is formulated, and the dynamics behaviors of the model under pulse vaccination are analyzed. By use of the discrete dynamical system determined by the stroboscopic map, an ‘infection-free＇ periodic solution is obtained, further, it is shown that the ‘infection-free＇ periodic solution is globally attractive when some parameters of the model are under appropriate conditions. Using the theory on delay functional and impulsive differential equation, the sufficient condition with time delay for the permanence of the system is obtained, and it is proved that time delays, pulse vaccination and vertical transmission can bring obvious effects on the dynamics behaviors of the model. The results indicate that the delay is ‘profitless’.

Compensation Algorithm Based on Estimation State for Transmission Delay in Cooperative Localization

In order to maximize the utilization of the observation information in the cooperative localization,a compensation algorithm based on the estimation state is presented for transmission delay.Under the framework of the Kalman filter,two different processes of state estimating with and without transmission delay are investigated and contrasted.The expression of difference quantity caused by transmission delay is derived.It is used to compensate the present estimation state instead of the observed information compensation.According to the characteristics of state transition matrix,an equivalent expression of which successively impacts on the covariance factor in delay time is obtained.The simulation results show that the present estimated state is effectively corrected by transmission information and the relevance among agents is accurately updated.As a result,a higher positioning accuracy is achieved.Meanwhile,the consumption of recording and multiplication of the state transition matrix is saved.

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.

A consensus time synchronization protocol in wireless sensor network

Time synchronization is one of the base techniques in wireless sensor networks(WSNs).This paper proposes a novel time synchronization protocol which is a robust consensusbased algorithm in the existence of transmission delay and packet loss.It compensates for transmission delay and packet loss firstly,and then,estimates clock skew and clock offset in two steps.Simulation and experiment results show that the proposed protocol can keep synchronization error below 2μs in the grid network of 10 nodes or the random network of 90 nodes.Moreover,the synchronization accuracy in the proposed protocol can keep constant when the WSN works up to a month.

Generation of Low-Delay and High-Stability Multicast Tree

Delay and stability are two key factors that affect the performance of multicast data transmission in a network.However,current algorithms of tree generation hardly meet the requirements of low delay and high sta-bility simultaneously.Given a general network,the generation algorithm of a multicast tree with minimum delay and maximum stability is an NP-hard problem,without a precise and efficient algorithm.To address these challenges,this paper studies the generation of low-delay and high-stability multicast trees under the model of spanning tree based on stability probability,degree-constrained,edge-weighted for multicast(T-SDE).A class of algorithms was proposed which creates the multicast tree greedy on the ratio of fan-out to delay(RFD)and probability of stability of terminal to obtain a high performance in multicast.The proposed algorithms greedily select terminals with a large RFD and a high probability of stability as forwarding nodes in the generation of the multicast tree,where the larger RFD and higher stability of upstream nodes are beneficial to achieve a low transmission delay and high stability in multicast.The proposed RFD can be compatible with the original model,which can take advantage of network connectivity during the generation of a multicast tree.This paper carries out simulation experiments on Matlab R2016b to measure the performance of the proposed algorithm.Experimental results show that the proposed algorithm can provide a smaller height,higher stability,and a lower transmission delay of the resulting multicast tree than other solutions.The spanning tree of the proposed algorithms can support low transmission delay and high stability in multicast transmission.

(α,β)-constraints connected dominating set algorithm in wireless sensor network

To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints is proposed. Based on the （α, β）-tree concept, a new connected dominating tree with bounded transmission delay problem（CDTT） is defined and a corresponding algorithm is designed to construct a CDT-tree which can trade off limited total power and bounded transmission delay from source to destination nodes. The CDT algorithm consists of two phases： The first phase constructs a maximum independent set（MIS）in a unit disk graph model. The second phase estimates the distance and calculates the transmission power to construct a spanning tree in an undirected graph with different weights for MST and SPF, respectively. The theoretical analysis and simulation results show that the CDT algorithm gives a correct solution to the CDTF problem and forms a virtual backbone with（ α,β）-constraints balancing the requirements of power consumption and transmission delay.

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.

Study on Robust H_∞ Filtering in Networked Environments

This paper is concerned with the robust H ∞ filter problem for networked environments, which are subject to both transmission delay and packet dropouts randomly. By employing random series which have Bernoulli distributions taking value of 0 or 1, the data transmission model is obtained. Based on state augmentation and stochastic theory, the sufficient condition for robust stability with H ∞ constraints is derived for the filtering error system. The robust filter is designed in terms of feasibility of one certain linear matrix inequality （LMI）, which is formed by adopting matrix congruence transformations. A numerical example is given to show the effectiveness of the proposed filtering method.

Stability analysis and stabilization of wireless networked control systems based on deadband control scheduling

The stability analysis and stabilization problems of the wireless networked control systems(WNCSs) with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the controller and the controller to the actor sides in the WNCS, which were used to reduce data transmission, furthermore, to decrease the network collision and node energy consumption. Under the consideration of time-varying delays and signal transmission deadbands, the model for the WNCS was presented. A novel Lyapunov functional which took full advantages of the network factors was exploited. Meanwhile, new stability analysis and stabilization conditions for the WNCS were proposed, which described the relationship of the delay bounds, the transmission deadband bounds and the system stability. Two examples were used to demonstrate the effectiveness of the proposed methods. The results show that the proposed approach can guarantee asymptotical stability of the system and reduce the data transmission effectively.

A routing algorithm for industrial wireless network based on ISA100.11a

ISA100.11 a industrial wireless network standard is based on a deterministic scheduling mechanism.For the timeslot delay caused by deterministic scheduling,a routing algorithm is presented for industrial environments.According to timeslot,superframe,links,channel and data retransmission of deterministic scheduling mechanisms that affect the design of the routing algorithm,the algorithm selects the link quality,timeslot delay and retransmission delay as the routing criteria and finds the optimum communication path by k shortest paths algorithm.Theoretical analysis and experimental verification show that the optimal paths selected by the algorithm not only have high link quality and low retransmission delay,but also meet the requirements of the deterministic scheduling.The algorithm can effectively solve the problem of packet loss and transmission delay during data transmission,and provide a valuable solution for efficient data transmission based on determinacy.

Non-PLL high-precision synchronous sampling method among lots of acoustics acquisition channels for underwater multilinear array seismic exploration system

Synchronous sampling is very essential in underwater multilinear array seismic exploration system in which every acquisition node(AN)samples analog signals by its own analog-digital converter(ADC).Aiming at the problems of complex synchronous sampling method and long locking time after varying sampling rate in traditional underwater seismic exploration system,an improved synchronous sampling model based on the master-slave synchronous model and local clock asynchronous drive with non phase locked loop(PLL)is built,and a high-precision synchronous sampling method is proposed,which combines the short-term stability of local asynchronous driving clock with the master-slave synchronous calibration of local sampling clock.Based on the improved synchronous sampling model,the influence of clock stability,transmission delay and phase jitter on synchronous sampling error is analyzed,and a high-precision calibration method of synchronous sampling error based on step-by-step compensation of transmission delay is proposed.The model and method effectively realize the immunity of phase jitter on synchronous sampling error in principle,and compensate the influence of signal transmission delay on synchronous sampling error.At the same time,it greatly reduces the complexity of software and hardware implementation of synchronous sampling,and solves the problem of long locking time after changing the sampling rate in traditional methods.The experimental system of synchronous sampling for dual linear array is built,and the synchronous sampling accuracy is better than 5 ns.

Synchronization transition of a modular neural network containing subnetworks of different scales

Time delay and coupling strength are important factors that affect the synchronization of neural networks.In this study,a modular neural network containing subnetworks of different scales was constructed using the Hodgkin–Huxley(HH)neural model;i.e.,a small-scale random network was unidirectionally connected to a large-scale small-world network through chemical synapses.Time delays were found to induce multiple synchronization transitions in the network.An increase in coupling strength also promoted synchronization of the network when the time delay was an integer multiple of the firing period of a single neuron.Considering that time delays at different locations in a modular network may have different effects,we explored the influence of time delays within each subnetwork and between two subnetworks on the synchronization of modular networks.We found that when the subnetworks were well synchronized internally,an increase in the time delay within both subnetworks induced multiple synchronization transitions of their own.In addition,the synchronization state of the small-scale network affected the synchronization of the large-scale network.It was surprising to find that an increase in the time delay between the two subnetworks caused the synchronization factor of the modular network to vary periodically,but it had essentially no effect on the synchronization within the receiving subnetwork.By analyzing the phase difference between the two subnetworks,we found that the mechanism of the periodic variation of the synchronization factor of the modular network was the periodic variation of the phase difference.Finally,the generality of the results was demonstrated by investigating modular networks at different scales.

Quantized H_∞ Fault-tolerant Control for Networked Control Systems

Quantized H_∞ fault-tolerant control for networked control systems (NCSs) with partial actuator fault with respect to actuators is concerned in this paper. Considering transmission delay, packet dropout and quantization, a synthesis model with partial actuator fault is established. The piecewise constant controller is adopted to model NCS with the transmission delay and packet dropout. Due to data transmitted in practical NCSs should be quantized before they are sent to the next network node, the logarithmic static and time-invariant quantizers at the sensor and controller sides are proposed in the paper. For the established model, an appropriate type of Lyapunov functions is provided to investigate the delay-dependent H_∞ control problem. According to an optimal problem, the controller that makes the system achieve the best performance is designed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.

High efficient multipacket decoding approach for network coding in wireless networks

To improve the performance of transmission by reducing the number of transmission and network overhead of wireless single-hop networks, this paper presents a high efficient multipacket decoding approach for network coding （EMDNC） in wireless networks according to the idea of encoding packets which cannot be decoded and are stored in buffer by receiving nodes, the lost packets can be recovered from these encoded packets. Compared with the network coding wireless broadcasting retransmission （NCWBR）, EMDNC can improve the efficiency of decoding and reduce the number of retransmission and transmission delay. Simulation results reveal that EMDNC can effectively reduce the number of retransmission and network overhead.

Call admission control scheme for real-time services in packet-switched OFDM wireless networks

A call admission control scheme is proposed for real-time services in packet-switched orthogonal frequency division multiplexing （OFDM） wireless cellular networks. The main idea of the proposed scheme is to use maximum acceptance ratio to maintain maximum channel utilization for real-time services according to the desired packet-level and call- level quality-of-service （QoS） requirements. The acceptance ratio is periodically adjusted by using a time discrete Markov chain and Wiener prediction theory according to the varying traffic load. Extensive simulation results show that this algorithm maintains high channel utilization, even as it guarantees packet-level and call-level QoS requirements for real-time services.