Delay Information Research Articles

An efficient model for robust load frequency control in multi-area power systems with communication delays

This paper proposes an effective method such that the robust load frequency control (LFC) scheme can be designed efficiently for the large-scale power system with time delay. A novel constraint time-delayed ordinary differential equation (CTODE) model is proposed, based on which a new bounded real lemma (BRL) is established for the H∞ performance analysis. The CTODE model is investigated considering the small number of remote signals influenced by delays in the LFC scheme. It consists of three parts, i.e., a delayed part includes the remote states, whose order is far less than that of the original system and remains unchanged with the increased scale of the power system, and a delay-free (related) part involves the local signals irrelevant (subjected) to the delayed states. Then, the BRL is established by constructing a new Lyapunov functional where the delayed part is employed to address the delay information. Case studies are implemented on the three-area LFC scheme and 39 bus New England systems. Compared with the existing methods, the developed BRL is available for the stability analysis with minor conservatism, but the calculation complexity is greatly reduced in large-scale power systems. Moreover, based on the CTODE model and original model, the robust controllers are designed and compared in robustness against load variations, time delays, and parameter uncertainties. Similar dynamic performance is verified for these two kinds of controllers through robust performance analysis, system eigenvalue analysis, and simulation studies.

Modelling the impact of rail delays on passenger satisfaction

Rail use and rail traffic in the UK increased substantially in the 25 years from 1994 to the end of 2019, a situation which led to progressively more delays and increasingly dissatisfied passengers. This study aims to quantify how disruptions to rail services are perceived by passengers to highlight situations that cause the highest rates of dissatisfaction so that they can be more effectively managed by the rail industry. Passenger satisfaction data from 7000 or so responses to the UK National Rail Passenger Survey (NRPS) where passengers had experienced delays were integrated with Network Rail data of the exact operational performance (e.g. train punctuality, service frequency, delay cause, magnitude of delay) that was encountered on each surveyed trip. An ordered logit model was then applied which allows for random taste variation to understand how passenger satisfaction was affected by rail delays. The study found that passengers reacted negatively to delays over 30 min, and dissatisfaction was exacerbated when passengers had to stand during the journey and/or received poor information, and when trains were cancelled. Policy implications for train operators include: (1) only cancel trains as a last resort; (2) prioritise trains approaching the ten minute delay threshold; (3) prioritise minimising delays to trains carrying high numbers of standing passengers; (4) enhance information quality and information delivery mechanisms as far as possible. Government should re-orientate franchise contracts to: (1) incentivise train operating companies to place more emphasis on passenger satisfaction when implementing service recovery strategies; and (2) improve delay information provision. Already the results are helping rail operators and practitioners to develop targeted recovery strategies aimed at minimising passenger dissatisfaction. This is the first academic study to investigate how rail passenger satisfaction is influenced by operational factors such as real-time delay, train frequency, train cancellations as well as delay causes.

Data-driven iterative tuning based active disturbance rejection control for FOPTD model

Active Disturbance Rejection Control (ADRC) emerges as a promising control method that can effectively handle uncertainties and disturbances. However, many model-based ADRC tuning methods turn laborious to achieve satisfactory control performance, when the critical process parameters are difficult to accurately obtain, especially the time delay information. To this end, this paper aims to propose a data-driven iterative tuning method for time-delayed ADRC (TD-ADRC). Based on parameter scaling technique, the quantitative correlation among control performance, robustness and normalized controller parameters are investigated. It is then used to design robust nominal controller. Then, based on the TD-ADRC inner-loop equivalent structure, an iterative feedback tuning (IFT) method is proposed to optimally obtain the nominal first order plus time delay (FOPTD) process model. Its unbiasedness and convergence are also described. With the empirical relations and the IFT stochastic approximation algorithm, a data-driven iterative tuning method for TA-ADRC is proposed, which allows a reasonable trade-off between system performance and robustness. Simulation results validate the efficacy of the proposed method, and a water-tank control experiment depicts a promising prospect in control practice.

Delay Risk Assessment Models for Road Projects

Significant universal research regarding causes of delay in road projects has been carried out based on expert opinion. This study classifies and standardizes all road construction delay factors found in the literature by developing a common risk breakdown structure (RBS) to allow for comparison between real project delay factors, and the study also proposes two delay risk assessment models (DRAMs) based on delay information from 120 real projects constructed in a similar environment with akin procurement and contract policies. The first calculates the risk priority number (RPN) and the second applies the Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) multi-criteria decision-making method (MCDM). The results showed that four specific delay factors dominate in Greek road construction for which relevant mitigation proposals are made. The proposed DRAMs, while calibrated for application in Greece, can be adapted to any construction environment for which real project data is available to provide a tool for transferring experience from past projects to future projects and from accomplished to novice public client decision makers.

RHNE-MAC: Random Handshake MAC Protocol Based on Nash Equilibrium for Underwater Wireless Sensor Networks

Underwater wireless sensor networks (UWSNs) have a long propagation delay; thus, when multiple nodes access the channel at the same time, the nodes cannot perceive the channel status in time, which causes access conflicts between nodes. To reduce multinode access conflicts and improve network throughput, a random handshake MAC protocol based on Nash equilibrium (RHNE-MAC) is proposed. In the RTS phase, RHNE-MAC regards nodes sending control packets to channels as competitive behavior and an incomplete information game. This paper firstly discusses the collision probability of two nodes sending data to the master node at the same time when the nodes are evenly distributed. Subsequently, according to the collision probability and the size of the network, the mathematical expectation concept is added to the payment function. Then, it uses the Nash equilibrium theory to solve the game, which allows the network to dynamically adjust the probability of nodes requesting access to a channel according to the number of nodes, thereby minimizing the problem of multinode access conflicts. Finally, the master node schedules the data transmission for each node according to the successful receipt of control packet information and propagation delay information of the network; therefore, multiple nodes can transmit data after a handshake period. The simulation results show that the throughput is increased by approximately 12% compared with prescheduling-based MAC and by 207% compared with TDMA; moreover, the end-to-end delay also has better performance.

Enhanced Stability Criteria of Network-Based Load Frequency Control of Power Systems with Time-Varying Delays

The stability problem for load frequency control (LFC) of power systems with two time-varying communication delays is studied in this paper. The one-area and two-area LFC systems are considered, respectively, which are modeled as corresponding linear systems with additive time-varying delays. An improved stability criterion is proposed via a modified Lyapunov-Krasovskii functional (LKF) approach. Firstly, an augmented LKF consisting of delay-dependent matrices and some single-integral items containing time-varying delay information in two different delay subintervals is constructed, which makes full use of the coupling information between the system states and time-varying delays. Secondly, the novel negative definite inequality equivalent transformation lemma is used to transform the nonlinear inequality to the linear matrix inequality (LMI) equivalently, which can be easily solved by the MATLAB LMI-Toolbox. Finally, some numerical examples are presented to show the improvement of the proposed approach.

Multivariate Curve Resolution Slicing of Multiexponential Time-Resolved Spectroscopy Fluorescence Data.

Time-resolved fluorescence spectroscopy (TRFS), i.e., measurement of fluorescence decay curves for different excitation and/or emission wavelengths, provides specific and sensitive local information on molecules and on their environment. However, TRFS relies on multiexponential data fitting to derive fluorescence lifetimes from the measured decay curves and the time resolution of the technique is limited by the instrumental response function (IRF). We propose here a multivariate curve resolution (MCR) approach based on data slicing to perform tailored and fit-free analysis of multiexponential fluorescence decay curves. MCR slicing, taking as a basic framework the multivariate curve resolution-alternating least-squares (MCR-ALS) soft-modeling algorithm, relies on a hybrid bilinear/trilinear data decomposition. A key feature of the method is that it enables the recovery of individual components characterized by decay profiles that are only partially describable by monoexponential functions. For TRFS data, not only pure multiexponential tail information but also shorter time delay information can be decomposed, where the signal deviates from the ideal exponential behavior due to the limited time resolution. The accuracy of the proposed approach is validated by analyzing mixtures of three commercial dyes and characterizing the mixture composition, lifetimes, and associated contributions, even in situations where only ternary mixture samples are available. MCR slicing is also applied to the analysis of TRFS data obtained on a photoswitchable fluorescent protein (rsEGFP2). Three fluorescence lifetimes are extracted, along with the profile of the IRF, highlighting that decomposition of complex systems, for which individual isomers are characterized by different exponential decays, can also be achieved.

New results for T-S fuzzy systems with hybrid communication delays

This paper deals with the stability problem of T-S fuzzy systems (TSFSs) with hybrid communication delays (HCDs). Compared with traditional communication delays, HCDs with Bernoulli distributed white noise sequences not only involve probabilistic discrete time-varying delays but also random additive time-varying delays (ATVDs). Based on the delay-product-type function (DPTF) and the second derivative method, a novel Lyapunov-Krasovskii functional (LKF) is developed, which fully considers the information of various communication delays. Moreover, by using novel integral inequalities and stochastic analysis theory, new stabilization criteria are established. Meanwhile, the desired fuzzy state feedback controller with HCDs and parallel distributed compensation (PDC) is designed by solving a set of linear matrix inequalities (LMIs). In the end, the usefulness of the obtained theoretical results is illustrated through two numerical simulation examples.

A Monitoring System for Transboundary Foot and Mouth Disease (FMD) considering the Demographic Characteristics in Gairo, Tanzania

Foot and Mouth Disease (FMD) is present in many countries, including Tanzania. Gairo is among the districts that frequently face FMD. This study found that the current mechanism for communicating FMD in Gairo district suffers from a long chain of information flow that causes delay and insufficient information for FMD control. Therefore, this study aimed to explore the implementation of an information system named "Monitoring System for Transboundary Foot and Mouth Disease," developed purposely to provide a standard platform for communicating FMD between livestock keepers and other stakeholders in the district. The system enables timely sharing of FMD events such as outbreaks, precaution measures, clinical signs, and negative impacts using Short Message Services (SMS), Unstructured Supplementary Service Data (USSD), and Voice Calls (robo-calls) through the mobile phones. Also, livestock keepers may report FMD outbreaks direct to the system using feature phones. The Statistical Package for Social Sciences (SPSS) was used to analyze data and Microsoft Visio was used for drawing the system architecture and information flow diagram. Finally, the system was implemented using PHP hypertext processor, JQuery, HTML, JSON, JavaScript, MySQL, and Apache webserver.

Stabilization to Exponential Input-to-State Stability of a Class of Neural Networks with Delay by Observer-Based Aperiodic Intermittent Control

This study is devoted to investigating the stabilization to exponential input-to-state stability (ISS) of a class of neural networks with time delay and external disturbances under the observer-based aperiodic intermittent control (APIC). Compared with the general neural networks, the state of the neural network investigated is not yet fully available. Correspondingly, an observer-based APIC is constructed, and moreover, neither the observer nor the controller requires the information of time delay. Then, the stabilization to exponential ISS of the neural network is realized severally by the observer-based time-triggered APIC (T-APIC) and the observer-based event-triggered APIC (E-APIC), and corresponding criteria are given. Furthermore, the minimum activation time rate (MATR) of the observer-based T-APIC and the observer-based E-APIC is estimated, respectively. Finally, a numerical example is given, which not only verifies the effectiveness of our results but also shows that the observer-based E-APIC is superior to the observer-based T-APIC and the observer-based periodic intermittent control (PIC) in control times and the minimum activation time rate, and the function of the observer-based T-APIC is also better than the observer-based PIC.

Nonfragile Sampled-Data Filtering of Uncertain Fuzzy Systems With Time-Varying Delays

This article studies the nonfragile sampled-data filtering problems for Takagi-Sugeno fuzzy systems with uncertainties and delays. By introducing two delay-product-type terms and other augmented terms, a novel Lyapunov-Krasovskii functional containing more detailed information of time delays is constructed. With the help of some new bounding inequalities, improved stability results for the addressed systems are established. Besides, a resilient sampled-data controller is devised with less cost. Furthermore, the efficiency of the obtained criteria is illustrated by a numerical example.

Modified Interpolation Method of Multi-Reference Station Tropospheric Delay Considering the Influence of Height Difference

In network real-time kinematic (NRTK) positioning, atmospheric delay information is critical for generating virtual observations at a virtual reference station (VRS). The traditional linear interpolation method (LIM) is widely used to obtain the atmospheric delay correction. However, even though the conventional LIM is robust in the horizontal direction of the atmospheric error, it ignores the influence of the vertical direction, especially for the tropospheric error. If the height difference between the reference stations and the rover is large and, subsequently, tropospheric error and height are strongly correlated, the performance of the traditional method is degraded for tropospheric delay interpolation at the VRS. Therefore, considering the height difference between the reference stations and the rover, a modified linear interpolation method (MLIM) is proposed to be applied to a conventional single Delaunay triangulated network (DTN). The systematic error of the double-differenced (DD) tropospheric delay in the vertical direction is corrected first. The LIM method is then applied to interpolate the DD tropospheric delay at the VRS. In order to verify the performance of the proposed method, we used two datasets from the American NOAA continuously operating reference stations (CORS) network with significant height differences for experiments and analysis. Results show that the DD tropospheric delay interpolation accuracy obtained by the modified method is improved by 84.1% and 69.6% on average in the two experiments compared to the conventional method. This improvement is significant, especially for low elevation satellites. In rover positioning analysis, the traditional LIM has a noticeable systematic deviation in the up component. Compared to the conventional method, the positioning accuracy of the MLIM method is improved in the horizontal and vertical directions, especially in the up component. The accuracy of the up component is reduced from tens of centimeters to a few centimeters and demonstrates better positioning stability.

State-based event-triggered consensus strategy for Takagi–Sugeno fuzzy fractional-order multiagent systems with switching topologies

This article addresses the event-triggered consensus problem for Takagi–Sugeno fuzzy fractional-order multiagent systems with switching topologies. First, to effectively avoid the frequent communication among agents, a state-based event-triggered consensus strategy is designed, which uses the local information from neighboring agents at sampling moments. Then, several sufficient conditions, which rely on the fractional derivative number and time delay information, are presented to guarantee the consensus of fractional-order multiagent systems based on Takagi–Sugeno fuzzy model. Moreover, Zeno behaviors are precluded by proving that the interval length of the two consecutive event-triggering moments for each agent is greater than a positive constant. Finally, some numerical examples are presented, which not only demonstrated the rationality of our proposed consensus protocol but also shown that the presented consensus method based on the designed event-triggered control protocol has the advantage for avoiding communication congestion compared to the existing results.

A sufficient negative‐definiteness condition for cubic functions and application to time‐delay systems

AbstractThis article studies the delay‐dependent stability of systems with a time‐varying delay. To get a stability criterion described as linear matrix inequalities (LMIs) from a positive definite Lyapunov‐Krasovskii functional (LKF), the negative‐definiteness condition, guaranteeing the negative definiteness of the derivative of the LKF, is necessary. This article proposes a negative‐definiteness lemma for the cubic function with respect to the time‐varying delay, which achieves the negative‐definiteness requirement without introducing any decision variable and extending the size of the LMIs contained in a stability criterion. Then benefiting from this lemma, an LKF with more delay information is constructed and applied to the stability analysis. After that, a delay‐dependent stability criterion is derived based on the LKF and the negative‐definiteness lemma. Finally, the contribution of the proposed lemma and the stability criterion is demonstrated with two examples.

A parallel learning particle swarm optimizer for inverse kinematics of robotic manipulator

In this study, a novel parallel learning particle swarm optimizer (PLPSO) is proposed. The evolutionary strategy of the algorithm is quite different from that of the existing PSO algorithms. To enhance the global search capability of the particle swarm, the original particle swarm is divided into two parallel evolving independent particle subpopulations to explore the search space simultaneously. In addition, according to the evolutionary factor in each iteration, the poorly performing particles in the two subpopulations are spurred and learned to improve the search speed of the particle swarm. In the process of particle learning, delay information is added to the velocity update item to reduce the occurrence of local capture. Twenty-eight benchmark functions of CEC2013 are used to evaluate the performance of the proposed PLPSO algorithm. Numerous comparisons demonstrate that the performance of the PLPSO algorithm is better than that of other nine PSO algorithms. Afterwards, the PLPSO algorithm is applied to the inverse kinematics (IK) solution of a robotic manipulator. By comparing with other three intelligent algorithms, the PLPSO algorithm shows an excellent performance in solving the IK problem. Finally, tests are carried out on an UR5 manipulator to confirm the practicability of the proposed PLPSO algorithm further. Thus, the feasibility of using the PLPSO algorithm for solving the IK problem of a robotic manipulator is verified.

Event-triggered synchronization for semi-Markov jump complex dynamic networks with time-varying delay

This paper investigates the event-triggered synchronization of complex dynamic networks (CDNs) with semi-Markov switching and time-varying delay. First, by proposing auxiliary vectors with a few nonorthogonal polynomials, two slack-matrix-based integral inequalities are formulated, which encompass some existing ones as special cases. Second, a triple-integral-based delay-product-type (TIDPT) Lyapunov-Krasovskii functional (LKF) is formulated, which fully utilizes the information of time delay. After designing a controller via the event- triggered scheme, some sufficient conditions are proposed to achieve the global stochastic synchronization by utilizing the reciprocally convex matrix inequality (RCMI) and the founded inequalities to evaluate the derivative of the established LKF. A numerical example is employed to show the effectiveness and practicability of the proposed method.

Bar code reader for the THz region.

We demonstrate a bar code sensing system for the THz region using leaky parallel plate waveguide and an off-axis parabolic mirror. The bars of the bar code are made from metal with air as gaps between them. We use up to 6 bars in the barcode system which can store up to 64 bits. Because the system employs coherent detection, we can further increase the bit density by adding Teflon strips to the barcode, encoding information in both amplitude and phase delay. These bar codes can be manufactured easily and inexpensively, offering a versatile alternative to RFID tags.

Distributed resilient state estimation for nonlinear systems with randomly occurring communication delays and missing measurements

SummaryThis article is concerned with the distributed H∞ resilient state estimation problem for a class of nonlinear systems with randomly occurring communication delays and missing measurements in sensor networks. A novel sensor model is proposed, in which two Bernoulli distributed white sequences are introduced to describe the random communication delay and missing measurements in a unified framework. Meanwhile, the estimator gain is allowed to fluctuate within a certain range. Based on the developed model, a novel Lyapunov–Krasovskii functional with multiple delay information terms is constructed, then the stochastic analysis technique and the extended integral inequality are used to calculate the functional derivative. Consequently, the existence conditions for the required distributed estimator are established to ensure that the estimation error system is asymptotically mean‐square stable and satisfies the prescribed H∞ performance constraint, and the desired gain of distributed resilient estimator is also solved by linearizing the nonlinear terms. Finally, a numerical example is given to illustrate the effectiveness of the proposed algorithm.

Extended dissipativity state estimation for generalized neural networks with time-varying delay via delay-product-type functionals and integral inequality

In this paper, the problem of extended dissipativity state estimation for delayed generalized neural networks (GNNs) is investigated. Firstly, in order to facilitate the use of more information of time-varying delay, a class of delay-product-type Lyapunov-Krasovskii functional (LKF) is proposed. Secondly, in order to accurately estimate the upper bound of the time-derivative of the constructed LKF, a delay-product-type integral inequality is proposed, then some sufficient conditions are obtained to guarantee the extended dissipativity state estimation for delayed GNNs. Moreover, the extended dissipativity state estimation can be used to tackle the problem of H∞ performance state estimation, passivity performance state estimation, L2-L∞ performance state estimation, and (Q,S,R)-γ-dissipativity state estimation for delayed GNNs. Finally, simulations are provided to illustrate the effectiveness of the proposed method.

Internet of Planets (IoP): A New Era of the Internet

Internet of Planets (IoP) is a concept that enables solar planets to communicate with each other using the Internet. While there is a plethora of research on IoP, the delay-tolerant network (DTN) has emerged as the most advanced technology in recent years. DTN is an asynchronous networking technology that has been deployed for the networking environment in which steady communication paths are not available, and therefore, it stores receiving data in a data storage and forward them only when the communication links are established. DTN can be applied to sensor networks and the mobile ad-hoc network, as well as space communication that supports data transmissions among satellites. In DTN networking environments, it is crucial to secure a scheme that has relatively low routing overhead and high reliability to achieve efficiency. Thus, this article proposes a time (delay) information based DTN routing scheme, which is able to predict routing paths for achieving efficient data transmissions among the nodes that have comparatively periodic moving patterns. The results of the proposed DTN routing algorithm using NS-3 simulation tools indicate satisfied levels of routing performance in comparison with the existing DTN algorithm.