Bound Of Delay Research Articles

Robust Path Diversity for Network Quality of Service in Cyber-Physical Systems

The reliability of control in cyber-physical systems (CPSs) heavily depends on the network-induced delay. The problem of obtaining a maximum allowable delay bound has been widely studied in the networked control systems (NCS) area. Once the delay bound is derived, the remaining question is how to make a network satisfy the bound. In this paper, we propose a robust path selection algorithm, which exploits multipath diversity for providing robust network performance against intrinsic randomness in delay. Our path selection algorithm gives the required paths for any given robustness level parameterized by the reliability violation probability. Based on extensive experimental results with our testbed, we empirically show that the proposed scheme can provide the required network quality of service (QoS) for system robustness.

Consensus tracking control of multi‐agent systems with an active virtual leader: time delay case

This paper studies the consensus tracking issue of second-order multi-agent systems with an active virtual leader and time delays. We aim to seek the upper bound of time delay τ * such that the multi-agent systems can achieve the consensus tracking for τ ∈ [0, τ *). Different methods such as Lyapunov–Razumikhin theory, Hopf bifurcation theory and matrix analysis method are employed to establish the corresponding consensus tracking criteria for continuous-time and discrete-time multi-agent systems, respectively. Finally, numerical examples are given to show the effectiveness of our theoretical results.

Average Consensus in Directed Networks of Multi-agents with Uncertain Time-varying Delays

This paper investigates the average consensus problem in directed networks of multi-agent systems with uncertain time-varying delays. Fixed and switching topologies that are kept weakly connected and balanced are firstly analyzed. The original system is then transformed into a reduced dimension model. Based on Jensen's inequality and reciprocally convex approach, sufficient conditions for average consensus are further presented. Specially, a less conservative upper bound of time-varying communication delays is derived in comparison with the existing results. Numerical examples confirm the effectiveness of the proposed method.

Bayesian Quickest Change-Point Detection With Sampling Right Constraints

In this paper, Bayesian quickest change detection problems with sampling right constraints are considered. Specifically, there is a sequence of random vari ables whose probability density function will change at an unknown time. The goal is to detect such a change in a way such that a linear combination of the average detection delay and the false alarm probability is minimized. Two types of sampling right constrains are discussed. The first one is a li mited sampling right constraint, in which the observer can take at most N observations from this random sequence. Under this setup, we show that the cost function can be written as a set of iterative fun ctions, which can be solved by Markov optimal stopping theory. The optimal stopping rule is shown to be a threshold rule. An asymptotic upper bound of the average detection delay is developed as the false alarm probability goes to zero. This upper bound indicates that the performance of the limited sampling right problem is close to that of the classic Bayesian quickest detection for several scenar ios of practical interest. The second constraint discussed in this paper is a stochastic sampling right const raint, in which sampling rights are consumed by taking observations and are replenished randomly. The observer cannot take observations if there are no sampling rights left. We characterize the optimal solution, which has a very complex structure. For practical applications, we propose a low complexity algorithm, in which the sampling rule is to take observations as long as the observer has sampling rights left and the detection scheme is a threshold rule. We show that this low complexity scheme is first order as ymptotically optimal as the false alarm probability goes to zero.

Nonfragile Control With Guaranteed Cost of T–S Fuzzy Singular Systems Based on Parallel Distributed Compensation

This paper investigates the nonfragile-guaranteed cost control problem for a class of uncertain nonlinear singular state-delayed systems that is described by Takagi-Sugeno models. The upper bound of state delay is assumed to be available. A linear quadratic cost function is specified as the performance index of the closed-loop system. Attention is focused on the fuzzy state feedback controller design via parallel distributed compensation scheme, which not only guarantees the regular, impulse-free, and asymptotically stable of the closed-loop fuzzy singular delay system, but also provides an optimized upper bound of the guaranteed cost function for the possibility of feedback gain variation and all admissible uncertainties. All derived sufficient conditions are given in terms of linear matrix inequalities. Some numerical examples are provided to illustrate the effectiveness of the proposed design scheme.

Reliable Robust Control Design for Uncertain Mechanical Systems

In this article, we consider the problem of reliable H∞ control for a class of uncertain mechanical systems with input time-varying delay and possible occurrence of actuator faults. In particular, we assume that linear fractional transformation (LFT) uncertainty formulations appear in the mass, damping, and stiffness matrices. The main objective is to design a state feedback reliable H∞ controller such that, for all admissible uncertainties as well as actuator failure cases, the resulting closed-loop system is robustly asymptotically stable while satisfying a prescribed H∞ performance constraint. By constructing an appropriate Lyapunov–Krasovskii functional (LKF) and using linear matrix inequality (LMI) approach, a new set of sufficient conditions are derived in terms of LMIs for the existence of robust reliable H∞ controller. Further, Schur complement and Jenson's integral inequality are used to substantially simplify the derivation in the main results. The obtained results are formulated in terms of LMIs which can be easily verified by the standard numerical softwares. Finally, numerical examples with simulation result are provided to illustrate the applicability and effectiveness of the proposed reliable H∞ control scheme. The numerical results reveal that the proposed theory significantly improves the upper bound of time delays and minimum feasible H∞ performance index over some existing works.

The Improved Method of Delay-Dependent Stability Criterion for Uncertain Systems with Multiple Time-Varying Delays

This paper discusses problems of linear uncertain system with multiple time-varying delays. Through the application of a novel design by own lemma and augmented Lyapunov function, a less conservative results than the existing essay that have been obtained. The new criterion enlarges the existing maximum bound of the time delay. Numerical examples were given to demonstrate the effective of the result.

New approach to stability criteria for generalized neural networks with interval time-varying delays

Abstract This paper is concerned with the problem of delay-dependent stability of delayed generalized continuous neural networks, which include two classes of fundamental neural networks, i.e., static neural networks and local field neural networks, as their special cases. It is assumed that the state delay belongs to a given interval, which means that the lower bound of delay is not restricted to be zero. An improved integral inequality lemma is proposed to handle the cross-product terms occurred in derivative of constructed Lyapunov–Krasovskii functional. By using the new lemma and delay partitioning method, some less conservative stability criteria are obtained in terms of LMIs. Numerical examples are finally given to illustrate the effectiveness of the proposed method over the existing ones.

Delay minimization by exploring full-duplex capacity and relay-based cooperative scheduling in WLANs

The research breakthrough on the hardware implementation of wireless full-duplex transmission has attracted significant interests on building full-duplex wireless networks in recent years. However, due to the asymmetry of real traffic flows, it is challenging to improve the network performance by effectively utilizing the full-duplex capacity. In this paper, we investigate the transmission delay minimization problem of full-duplex WLANs under ad-hoc mode. We first derive a lower bound of the total transmission delay and then propose a relay-based cooperative schedule scheme named CR-Mechanism, via exploiting eligible full-duplex communication opportunities. Our theoretical analysis shows that it achieves such lower bound with a polynomial-time complexity. Furthermore, the closed-form expressions of the expectation of totaly delay, time saving and transmission cost of CR-Mechanism are also derived. The extensive experimental results confirm that CR-Mechanism is an optimal scheduling algorithm with better performance than conventional mechanisms under different traffic models.

Synchronization of a class of uncertain stochastic discrete-time delayed neural networks

Abstract The global asymptotical synchronization problem is discussed for a general class of uncertain stochastic discrete-time neural networks with time delay in this paper. Time delays include time-varying delay and distributed delay. Based on the drive-response concept and the Lyapunov stability theorem, a linear matrix inequality (LMI) approach is given to establish sufficient conditions under which the considered neural networks are globally asymptotically synchronized in the mean square. Therefore, the global asymptotical synchronization of the stochastic discrete-time neural networks can easily be checked by utilizing the numerically efficient Matlab LMI toolbox. Moreover, the obtained results are dependent not only on the lower bound but also on the upper bound of the time-varying delays, that is, they are delay-dependent. And finally, a simulation example is given to illustrate the effectiveness of the proposed synchronization scheme.

Stochastic Sampled-Data Control for Exponential Synchronization of Markovian Jumping Complex Dynamical Networks with Mode-Dependent Time-Varying Coupling Delay

In this paper, we address the problem of exponential synchronization of Markovian jumping complex dynamical networks with mode-dependent time-varying coupling delay via a stochastic sampled-data controller. In addition, the sampling period is assumed to be time-varying and switches between $$m$$ m different values in a random way with given probability. By constructing a new Lyapunov---Krasovskii functional (LKF) with triple integral terms and by employing convex combination technique and free weighting matrices method, sufficient conditions for the coupled complex dynamical network to be globally exponentially synchronized in the mean square sense are derived. The information about the lower bound of the discrete time-varying delay is used in the LKF. Based on the derived condition, the desired sampled-data feedback controller is designed in terms of the solution to linear matrix inequalities. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

Bilateral Control and Stabilization of Asymmetric Teleoperators With Bounded Time-Varying Delays

A novel control scheme for asymmetric bilateral teleoperation systems is developed based on linear models of the hardware, with considerations in the existence of communication time delays. The master and slave manipulators were modeled as linear single degree of freedom systems. The human user force was modeled based on the band limited availability of human motion, and the environmental force was modeled as a spring and damper combination based on the slave position. The configuration of the whole system represents a relatively general framework for the teleoperation systems. The main contribution of the work can be concluded as follows. First to deal with asymmetric systems in teleoperation, an impedance matching approach was applied to the master side dynamics, while a static error feedback gain was used to stabilize the slave side dynamics. Second, in the existence of bounded random time-varying delays, approaches and techniques based on the Lyapunov method proposed for network controlled systems are now proposed for bilateral teleoperation systems. Specifically, a Lyapunov functional is proposed with consideration for the upper and lower bound of random delays. Linear matrix inequality (LMI) techniques are used with rigorous stability proof to design the slave side controller control gains. Furthermore, the cone complementarity algorithm is used to deal with nonlinear terms within the LMI under the new formulation. Finally, the applications of the proposed algorithm to haptic devices are described thoroughly, and experimental results with comparisons to simulation results are demonstrated to show the effectiveness of the proposed approach.

Exponential synchronization criteria for Markovian jumping neural networks with time-varying delays and sampled-data control

This paper deals with the problem of exponential synchronization of Markovian jumping neural networks with time-varying delays and variable sampling control. Several delay-dependent synchronization criteria are derived to ensure the convergence of the error systems, that is, the master systems stochastically synchronized with the slave systems. By employing an improved Lyapunov–Krasovskii functional (LKF) with the triple integral terms and combining the convex technique, two new sufficient conditions are derived to guarantee that a class of delayed neural networks (DNNs) to be globally exponentially stable. The information about the lower bound of the discrete time-varying delay is fully used in the LKF. Moreover, the conditions obtained in this paper are formulated in terms of linear matrix inequalities (LMIs), which can be efficiently solved via standard numerical software. The maximum sampling intervals are obtained based on the design of mode-independent controller. Finally, three numerical examples are given to demonstrate the efficiency of the proposed theoretical results.

Distributed receding horizon control of large-scale nonlinear systems: Handling communication delays and disturbances

This paper studies the robust distributed receding horizon control (DRHC) problem for large-scale continuous-time nonlinear systems subject to communication delays and external disturbances. A dual-mode robust DRHC strategy is designed to deal with the communication delays and the external disturbances simultaneously. The feasibility of the proposed DRHC and the stability of the closed-loop system are analyzed, and the sufficient conditions for ensuring the feasibility and stability are developed, respectively. We show that: (1) the feasibility is affected by the bounds of external disturbances, the sampling period and the bound of communication delays; (2) the stability is related to the bounds of external disturbances, the sampling period, the bound of communication delays and the minimum eigenvalues of the cooperation matrices; (3) the closed-loop system is stabilized into a robust invariant set under the proposed conditions. A simulation study is conducted to verify the theoretical results.

On centralized and distributed algorithms for minimizing data aggregation time in duty-cycled wireless sensor networks

We study the problem of minimizing data aggregation time in wireless sensor networks (WSNs) under the practical duty-cycle scenario where nodes switch between active states and dormant states periodically for energy efficiency. Under the protocol interference model, we show that the problem is NP-hard and present a lower bound of delay for any data aggregation scheme. To solve the problem efficiently, we then construct a routing tree based on connected dominator set and propose two aggregation scheduling algorithms, which are the centralized Greedy Aggregation Scheduling (GAS) and the distributed Partitioned Aggregation Scheduling (PAS), so as to generate collision-free transmission schedules for data aggregation in duty-cycled WSNs. To minimize the total delay, GAS tries to achieve maximal concurrent transmissions in each time-slot during each frame by using global information, while PAS leverages a network partition based strategy and local information to ensure the largest degree of channel reuse across space and time domains. Theoretical analysis indicates that each algorithm consumes at most $$O(R+\varDelta)$$ O ( R + Δ ) frames and achieves nearly constant factor approximation on the optimal delay. Here R and $$\varDelta$$ Δ are the network radius and the maximum node degree, respectively. We also evaluate the practicability of our algorithms by extensive simulations under various network conditions and the results corroborate our theoretical analysis.

On stability analysis for neural networks with interval time-varying delays via some new augmented Lyapunov–Krasovskii functional

This paper is concerned with the problem of stability analysis of neural networks with interval time-varying delays. It is assumed that the lower bound of time-varying delays is not restricted to be zero. By constructing a newly augmented Lyapunov–Krasovskii functional which has not been proposed yet and utilizing some integral information on activation function as elements of augmented vectors, an improved stability criterion with the framework of linear matrix inequalities (LMIs) is introduced in Theorem 1. Based on the result of Theorem 1 and utilizing the property of the positiveness of Lyapunov–Krasovskii functional, a further relaxed stability condition will be proposed in Theorem 2. The effectiveness and less conservatism of the proposed theorems will be illustrated via three numerical examples.

Concurrency testing using schedule bounding

We present the first independent empirical study on schedule bounding techniques for systematic concurrency testing (SCT). We have gathered 52 buggy concurrent software benchmarks, drawn from public code bases, which we call SCTBench. We applied a modified version of an existing concurrency testing tool to SCTBench to attempt to answer several research questions, including: How effective are the two main schedule bounding techniques, preemption bounding and delay bounding, at bug finding? What challenges are associated with applying SCT to existing code? How effective is schedule bounding compared to a naive random scheduler at finding bugs? Our findings confirm that delay bounding is superior to preemption bounding and that schedule bounding is more effective at finding bugs than unbounded depth-first search. The majority of bugs in SCTBench can be exposed using a small bound (1-3), supporting previous claims, but there is at least one benchmark that requires 5 preemptions. Surprisingly, we found that a naive random scheduler is at least as effective as schedule bounding for finding bugs. We have made SCTBench and our tools publicly available for reproducibility and use in future work.

Consensusability of multi-agent systems with time-varying communication delay

This paper studies the consensusability problem of continuous-time multi-agent systems with time-varying communication delay in undirected network. We design a consensus protocol based on the low gain solution of a parametric algebraic Riccati equation (ARE) and not use the precise information of the amount of time-varying delay. By studying the joint effect of agent dynamic and network topology, sufficient conditions are given for consensus when all poles of the system matrix are on the closed left-half plane. In case of non-zero poles on the imaginary axis, maximal admissible upper bound of the time-varying delay is given in terms of both the agent dynamic and network topology; otherwise, consensus can be achieved for the time-varying delay with arbitrarily large upper bound. Finally, simulation results are presented to demonstrate the effectiveness of the theoretical results.

Exponential synchronization of Markovian jumping neural networks with partly unknown transition probabilities via stochastic sampled-data control

This paper investigates the exponential synchronization for a class of delayed neural networks with Markovian jumping parameters and time varying delays. The considered transition probabilities are assumed to be partially unknown. In addition, the sampling period is assumed to be time-varying that switches between two different values in a random way with given probability. Several delay-dependent synchronization criteria have been derived to guarantee the exponential stability of the error systems and the master systems are stochastically synchronized with the slave systems. By introducing an improved Lyapunov–Krasovskii functional (LKF) including new triple integral terms, free-weighting matrices, partly unknown transition probabilities and combining both the convex combination technique and reciprocal convex technique, a delay-dependent exponential stability criteria is obtained in terms of linear matrix inequalities (LMIs). The information about the lower bound of the discrete time-varying delay is fully used in the LKF. Furthermore, the desired sampled-data synchronization controllers can be solved in terms of the solution to LMIs. Finally, numerical examples are provided to demonstrate the feasibility of the proposed estimation schemes from its gain matrices.

Monitoring procedure for parameter change in causal time series

We propose a new sequential procedure to detect change in the parameters of a process X=(Xt)t∈Z belonging to a large class of causal models (such as AR(∞), ARCH(∞), TARCH(∞), or ARMA–GARCH processes). The procedure is based on a difference between the historical parameter estimator and the updated parameter estimator, where both these estimators are quasi-likelihood estimators. Unlike classical recursive fluctuation test, the updated estimator is computed without the historical observations. The asymptotic behavior of the test is studied and the consistency in power as well as an upper bound of the detection delay is obtained. Some simulation results are reported with comparisons to some other existing procedures exhibiting the accuracy of our new procedure. This procedure coupled with retrospective tests is applied to solve off-line multiple breaks detection in the daily closing values of the FTSE 100 stock index.