Impact Of Communication Delays Research Articles

Learning Underwater Intervention Skills Based on Dynamic Movement Primitives

Improving the autonomy of underwater interventions by remotely operated vehicles (ROVs) can help mitigate the impact of communication delays on operational efficiency. Currently, underwater interventions for ROVs usually rely on real-time teleoperation or preprogramming by operators, which is not only time-consuming and increases the cognitive burden on operators but also requires extensive specialized programming. Instead, this paper uses the intuitive learning from demonstrations (LfD) approach that uses operator demonstrations as inputs and models the trajectory characteristics of the task through the dynamic movement primitive (DMP) approach for task reproduction as well as the generalization of knowledge to new environments. Unlike existing applications of DMP-based robot trajectory learning methods, we propose the underwater DMP (UDMP) method to address the problem that the complexity and stochasticity of underwater operational environments (e.g., current perturbations and floating operations) diminish the representativeness of the demonstrated trajectories. First, the Gaussian mixture model (GMM) and Gaussian mixture regression (GMR) are used for feature extraction of multiple demonstration trajectories to obtain typical trajectories as inputs to the DMP method. The UDMP method is more suitable for the LfD of underwater interventions than the method that directly learns the nonlinear terms of the DMP. In addition, we improve the commonly used homomorphic-based teleoperation mode to heteromorphic mode, which allows the operator to focus more on the end-operation task. Finally, the effectiveness of the developed method is verified by simulation experiments.

Assessing the impact of communication delays for Autonomous Intersection Management systems

Communication is essential for Cooperative Intelligent Transportation Systems (C-ITS) to achieve better road efficiency, especially for Autonomous Intersection Management (AIM) which coordinates vehicles to pass the intersection safely and efficiently. Communication delays cause severe safety crises (i.e., collisions) and vehicular-performance degradation regarding intersection capacities and vehicular delays. Targeting the delays, network researchers have been working on low-latency communication technologies, and C-ITS researchers have proposed delay-tolerant AIM systems to avoid collisions in intersections. The impacts of communication delays are observed and discussed in the literature; however, models and assessments of the delay requirements for AIM are needed to provide insights for future network and C-ITS research. Here, we model the impact of communication delays on vehicular performance at an autonomous intersection and validate the models with the simulation results from over two million experiments, two types of multi-lane intersections (a typical 4-legged intersection and a roundabout), and four AIM systems. The simulations are conducted with SUMO simulator and AIM systems, where communication delays are inserted into the message exchanges during the simulation. The models are represented in linear, quintic, and cubic polynomials, showing that communication delay between 0 to 100 milliseconds is linearly related to vehicular performance in terms of intersection capacity and vehicular delay. According to the models, we show that by reducing communication delay from 100 to 10 milliseconds, the capacity degradation can be reduced from 7-10% to 0.7-1.0%. Moreover, communication delays must be less than 247 milliseconds to allow AIM systems to outperform traditional traffic lights.

Swarm of Drones in a Simulation Environment—Efficiency and Adaptation

In the swiftly advancing field of swarm robotics and unmanned aerial vehicles, precise and effective testing methods are essential. This article explores the crucial role of software-in-the-loop (SITL) simulations in developing, testing, and validating drone swarm control algorithms. Such simulations play a crucial role in reproducing real-world operational scenarios. Additionally, they can (regardless of the type of application) accelerate the development process, reduce operational risks, and ensure the consistent performance of drone swarms. Our study demonstrates that different geometrical arrangements of drone swarms require flexible control strategies. The leader-based control model facilitates coherent movement and enhanced coordination. Addressing various issues such as communication delays and inaccuracies in positioning is essential here. These shortcomings underscore the value of improved approaches to collision avoidance. The research described in this article focused on the dynamics of drone swarms in a simulated context and emphasized their operational efficiency and adaptability in various scenarios. Advanced simulation tools were utilized to analyze the interaction, communication, and adaptability of autonomous units. The presented results indicate that the arrangement of drones significantly affects their coordination and collision avoidance capabilities. They also underscore the importance of control systems that can adapt to various situations. The impact of communication delays and errors in positioning systems on the required distance between drones in a grid structure is also presented. This article assesses the impact of different levels of GPS accuracy and communication delays on the coordination of group movement and collision avoidance capabilities.

Fixed-Time Coordinated Attitude Control for spacecraft formation flying via event-triggered and delayed communication

This article tackles the challenge of achieving fixed-time coordinated attitude control for spacecraft formation flying when dealing with event-triggered and delayed communication. First and foremost, we introduce a fixed-time observer that leverages event-triggered, time-delayed information to enable follower spacecraft to access the leader’s commands within a directed, switching topology. In particular, the observer possesses the ability to effectively mitigate the impact of communication delays on information propagation. Following this, a fixed-time controller that empowers each follower to precisely follow the leader’s trajectory while maintaining the formation configuration is devised. Ultimately, we validate the feasibility and superiority of the proposed algorithm through numerical simulations and practical spacecraft ground experiments conducted with planar air-floating robots.

Asynchronous distributed optimal power control for fatigue load minimization in wind farms

An asynchronous distributed optimal power control (OPC) scheme is proposed to minimize fatigue load in the wind farms (WFs) in this paper. To better satisfy the grid code, each wind turbine (WT) in the scheme is equipped with an energy storage system (ESS) at the DC link of the WT converter. Based on the WT topology, a WT-ESS control model is established, thus developing an OPC scheme to control the generator torque, pitch angle, and ESS output simultaneously for reducing fatigue load. By formulating the model predicted control (MPC)-based optimal problems, the virtual mechanical power control is proposed to regulate the ESSs output for clarifying the power interactions among WTs and ESSs. In order to achieve more effective control of the above three parameters among multiple WTs-ESSs, an asynchronous distributed alternating direction method of multipliers (AD-ADMM) is developed to simultaneously minimize the variations of thrust force, shaft torque, and flapping moment load of the WTs in a wider range. Considering the impact of communication delays, the proposed AD-ADMM algorithm has the higher time efficiency and system robustness. The convergence of the proposed AD-ADMM algorithm is analyzed, and several cases are used to validate the performance of the OPC scheme.© 2017 Elsevier Inc. All rights reserved.

Hierarchical Coordination Control for Interconnected Operation of Electric-thermal-gas Integrated Energy System with Micro-energy Internet Clusters

At present, the natural gas network, thermal network and power grid can be coupled in the integrated energy system(IES) to provide users with different forms of energy such as heat, electricity and gas, but the relevant coordinated control strategies have not been sufficiently investigated. In this paper, a hierarchical distributed coordinated control strategy is proposed. The system is organized into three levels, namely IES-level, Micro-energy Internet(MEI)-level and component-level based on multi-agent system approach. To achieve accurate control of voltage and frequency of distributed devices and accurate distribution of the tie-line power in case of load fluctuations in MEI, a second-level optimization controller based on distributed sparse communication network is designed. In addition, in order to analyze the impact of communication delay on the coordinated control of MEI-level agents, the communication topology is optimized according to the basic graph theory. Finally, taking IES with three MEIs as an example, the validity of the proposed control strategy is verified on the PSCAD/EMTDC simulation platform.

Formation control of fixed-wing UAVs with communication delay

Fixed-wing unmanned aerial vehicles (UAVs) possess high speed and non-hovering capabilities, rendering them uniquely advantages for reconnaissance and detection. The focus of this paper is to addressing the problem of formation control for fixed-wing UAVs in the presence of communication delay. To tackle this problem, for the non-holonomic kinematic model, we propose an intuitive and practical control law based on the leader-follower method to ensure that UAVs maintain a predetermined geometric formation. The stability analysis of the system with communication delay is conducted by constructing a strict Lyapunov–Krasovskii function. Furthermore, we consider the impact of communication delay on formation accuracy and present a prediction algorithm capable of forecasting the actual position of each UAV. To validate our theoretical findings, both digital simulation and hardware-in-loop experiment are conducted.

Formula omitted]-[formula omitted]-dissipative control of T-S fuzzy systems via aperiodic sampling control with communication delay

This article concerns the strict (Q,S,R)-γ dissipativity of Takagi–Sugeno fuzzy systems (TSFSs) via aperiodic sampled-data control with communication delay. The motivations of this paper are that the transmission channels have communication delay and the original dissipative analysis method may be conservative. In order to consider the impact of communication delays, first of all, a sampled-data controller (SDC) with a constant communication delay is conceived to analyze the dissipativity of TSFSs. Next, the overall closed-loop system model is established stemming from the designed controller. In order to attain less conservative results, a new looped-functional which can take advantage of the available information of the sampling instants is formed. Then, strict (Q,S,R)-γ dissipativity can be guaranteed by a criterion obtained by using the looped-functional and the modified free-matrix-based inequality (FMBI) technique. By working out the obtained linear matrix inequalities (LMIs), the controller gain matrix that meets the requirement can be determined. Finally, the truck trailer and the mass–spring systems are showcased as simulation examples to provide evidence of the effectivity and superiority of the devised approach. In the presence of 0.1 s communication delay in the truck trailer system controller, the maximum γ can reach 0.9751 when sampling interval h takes 0.15 s, which makes the system can achieve strict (Q,S,R)-γ dissipativity.

Fault Recovery Methods for a Converged System Comprised of Power Grids, Transportation Networks and Information Networks

Recently, triple-network convergence systems (TNCS) have emerged from the deep integration of the power grid, transportation networks, and information networks. Fault recovery research in the TNCS is important since this system’s complexity and interactivity can expand the fault’s scale and increase the fault’s impact. Currently, fault recovery focuses primarily on single power grids and cyber–physical systems, but there are certain shortcomings, such as ignoring uncertainties, including generator start-up failures and the occurrence of new faults during recovery, energy supply–demand imbalances leading to system security issues, and communication delays caused by network attacks. In this study, we propose a recovery method based on the improved twin-delayed deep deterministic algorithm (TD3), factoring in the shortcomings of the existing research. Specifically, we establish a TNCS model to analyze interaction mechanisms and design a state matrix to represent the uncertainty changes in the TNCS, a negative reward to reflect the impact of unit start-up failures, a special reward to reflect the impact of communication delay, and an improved actor network update mechanism. Experimental results show that our method obtains the optimal recovery decisions, maximizes restoration benefits in power grid failure scenarios, and demonstrates a strong resilience against communication delays caused by DoS attacks.

A DRL-Based Load Shedding Strategy Considering Communication Delay for Mitigating Power Grid Cascading Failure

Successive failures in power transmission lines can cause cascading failures in the power grid, which may eventually affect large parts of the power grid and even cause the power grid system to go down. Collecting and transmitting primary equipment information and issuing load-shedding action commands in the power grid depend on the power communication network. With the help of the power communication network, we can better observe the situation of the power grid in real time and provide a guarantee for the regular working of the power grid. However, the communication network also has the problem of communication delay causing latency in load-shedding action. On the premise of preserving the key physical properties and operational characteristics of the power grid, this paper uses the IEEE 14 and 30 bus systems as examples to establish a direct current (DC) power flow simulation environment. We establish a communication network model based on the power grid topology and the corresponding communication channels. For the problem of cascading failures occurring in the power grid after transmission line failures, a load-shedding strategy using soft actor-critic (SAC) based on deep reinforcement learning (DRL) was developed to effectively mitigate cascading failures in the power grid while considering the impact of communication delay. The corresponding communication delay is obtained by calculating the shortest communication path using the Dijkstra algorithm. The simulation verifies the feasibility and effectiveness of the SAC algorithm to mitigate cascading failures. The trained network can decide on actions and give commands quickly when a specific initial failure is encountered, reducing the scale of cascading failures.

Distributed elastic recovery strategy of AC/DC hybrid microgrid under false data injection attack

AbstractThe AC/DC hybrid microgrid, which integrates AC microgrid and DC microgrid, greatly improves the flexibility of distributed energy. However, it is imperative to acknowledge that the microgrid in question is accompanied by a significantly elevated network security risk. To solve this problem, this article proposes a false data injection attack detection and alarm method based on active power output. The detection algorithm is capable of detecting attacks at any location within the microgrid and mitigating the impact of communication delay. Moreover, a distributed elastic recovery strategy based on the aforementioned detection algorithm is proposed. This strategy aims to expeditiously restore the compromised agent to its rated state. Finally, a simulation model is developed to demonstrate the effectiveness of the proposed strategy.

Coordinated Power Oscillation Damping From a VSC-HVDC Grid Integrated With Offshore Wind Farms: Using Capacitors Energy

This paper proposes a novel coordinated control strategy for a voltage source converter (VSC) based high-voltage direct current (HVDC) grid integrated offshore wind farms (OWFs) to damp the power system oscillations. A feature of this strategy is aiming to use the DC-link capacitor energy of offshore wind turbines (WTs) to reduce interactions between power oscillations and HVDC grid voltage when onshore grid-side VSCs (GSVSCs) modulate the active and reactive power injections. Unlike the previous communication-based method, the coordination from offshore WTs in this strategy depends on the local measurements of the HVDC grid voltage instead of the remote communication data from the onshore AC grid. A modified IEEE 39-bus power system with a 5-terminal VSC-HVDC grid connected to two OWFs has been developed to validate the effectiveness of this proposed strategy. Both the eigenvalue analysis and time-domain simulation results indicate that this strategy can significantly improve the power oscillation damping (POD). Comparative simulation studies also conclude that the proposed strategy has similar POD improvements to the previous communication-based method without the negative impact of communication delay from onshore to offshore.

Braiding – A novel approach to supporting space/ground communication under signal latency

Braiding is a novel, text-based software designed to facilitate communication between crewmembers in space and mission support on Earth under signal latency. Its feasibility and benefits for text-based time-delayed communication were assessed in a Human-in-the loop (HITL) study involving flight surgeons FS/Mission Support personnel and former participants in space exploration analog simulations (Crew). The HITL evaluation was conducted online with pairs of volunteers (one crewmember and one FS/Mission Support personnel as MCC) collaborating under communication delay on operationally relevant task situations, contrasting a texting tool (functionally comparable to the one currently used in NASA analog missions) with braiding. Volunteers received fictional but realistic information for each task to help them perform in their assigned role (MCC or Crew). The study involved two test sessions over two days, each presenting participants with three task events. Data collected included participants' post-session ratings of their time-delayed communication and a 30–45 min exit interview. Quantitative analyses indicated that participants rated braiding more favorably than texting with respect to the quality of their time-delayed communication and its ability to mitigate the impact of communication delay and support teamwork. Qualitative analyses revealed that participants appreciated the affordances of braiding—that the software organized their conversation by topic, maintained the chronological order of related messages, and brought continuity and a natural feel to their conversation—but were less comfortable with some of its constraints. These findings suggest that braiding can be an effective communication tool under time delay and also point to specific training issues to ensure that users feel at ease not only with braiding's resources but also its medium-specific restrictions.

Special issue on “Optimal design and operation of energy systems”

Special issue on “Optimal design and operation of energy systems”

Maximum acceptable communication delay for the realization of telesurgery.

AimTo determine acceptable limits of communication delays in telesurgery, we investigated the impact of communication delays under a dynamic environment using a surgical assist robot. Previous studies have evaluated acceptable delays under static environments. Effects of delays may be enhanced in dynamic environments, but studies have not yet focused on this point.MethodsThirty-four subjects with different surgical experience (Group1: no surgical experience; Group2: only laparoscopic surgical experience; Group3: robotic surgery experience) performed 4 tasks under different delays (0, 70, 100, 150, 200, or 300 ms) using a surgical assist robot. Task accomplishment time and total movement distance of forceps were recorded and compared under different communication delays of 0–300 ms. In addition, surgical performance was compared between Group1or Group2 without delay and Group3 with communication delays.ResultsSignificant differences in task accomplishment time were found between delays of 0 and 70 ms, but not between delays of 70 and 100 ms. Thereafter, the greater the communication delay, the longer the task accomplishment time. Similar results were obtained in total movement distance of forceps. Comparisons between Group3 with delay and Group1 or Group2 without delay demonstrated that surgical performance in Group3 with delay was superior or equal to that of Group1 or Group2 without delay as long as the delay was 100 ms or less.ConclusionsCommunication delays in telesurgery may be acceptable if 100 ms or less. Experienced surgeons with more than 100 ms of delay could outperform less-experienced surgeons without delay.

An optimal sensor location based protection scheme for DER-integrated hybrid AC/DC microgrid with reduced communication delay

In spite of the advantages, the acceptance of hybrid microgrid has been hindered due to the complexity of the protection task. With increased number of DERs (Distributed Energy Resources) and loads in the network, the placement of sensors in every bus for proper monitoring and protection is often not economical both in terms of sensor installation cost and the cost associated with communication infrastructure. Transmission of high volume of sensor information through the communication network demands high bandwidth for reduced communication delay. In this regard, a low-cost protection scheme for hybrid microgrid with optimal sensor placement and immunity against converter faults has been proposed. The issues related to sensor placement and increased impact of communication delay of the reported techniques has been addressed by identifying a set of optimal sensor locations for network observability. The scheme based on Wavelet Packet Decomposition (WPD) and ensemble classifier has been extensively validated in terms of the optimality of identified sensor locations, minimization of communication delay and accuracy of the protection scheme.

Frequency Regulation Model of Bulk Power Systems With Energy Storage

This paper presents a Frequency Regulation (FR) model of a large interconnected power system including Energy Storage Systems (ESSs) such as Battery Energy Storage Systems (BESSs) and Flywheel Energy Storage Systems (FESSs), considering all relevant stages in the frequency control process. Communication delays are considered in the transmission of the signals in the FR control loop and ESSs, and their State of Charge (SoC) management model is considered. The system, ESSs and SoC components are modelled in detail from a FR perspective. The model is validated using real system and ESSs data, based on a practical transient stability model of the North American Eastern Interconnection (NAEI), and the results show that the proposed model accurately represents the FR process of a large interconnected power network including ESS, and can be used for long-term FR studies. The impact of communication delays and SoC management of ESS facilities in the Area Control Error (ACE) is also studied and discussed, as well as the computational efficiency of the proposed FR model.

Modeling Cascading Failures in Coupled Smart Grid Networks

The smart grid connects components of power systems and communication networks in an interdependent two-way system that delivers electricity to consumers and collects data that enables it to react to usage levels and interference from threats, such as cyber-attacks. In this paper, we propose a novel cyber-attack failure propagation model in smart grids. Our realistic failure propagation model addresses the system’s heterogeneity by assigning different roles to its components. We define rules for and interdependencies of failure propagation and propose a new approach to studying cascading failures. In addition, our graph model identifies the most-vulnerable nodes. The model implements power flow analysis to guarantee that all transmission lines work below capacity and remove lines exceeding capacity. The model also considers that control packets could encounter different delays regarding the communication network structure and investigates the impact of communication delay on the failure of power components. Our results establish that by considering both power and communication characteristics and interdependencies, cascading failures can be modeled more accurately. We show that when we run the power flow analysis, there are a negligible number of failed nodes, which means that our model accurately identifies system failures.

Distributed Control Scheme for Accurate Power Sharing and Fixed Frequency Operation in Islanded Microgrids

Global Positioning System (GPS) based control has recently been reported as a replacement of droop control to achieve fixed frequency operation in islanded microgrids. This article presents the perspective that the power sharing performance of a general microgrid synchronized by GPS is essentially determined by equivalent output impedance. A novel adaptive virtual impedance control approach, which implements different values of virtual resistance for d- and q-axis, is proposed accordingly. The virtual resistance concept is implemented comprising a basic local implementation for output impedance shaping, and a sparse resistance tuning network for the compensation of mismatched feeder impedance, which demands no knowledge of actual output impedance. The resistance tuning network utilizes the consensus protocol and only requires neighboring interactions among DG units. A complete tuning of output resistance for a given load condition results in accurate active and reactive power sharing even after communication is interrupted and will still outperform conventional droop control methods if load changes during the interruption. Small-signal analysis based on delay differential equations model of the overall microgrid is performed to investigate the adverse impact of communication delays on system stability. The efficacy of the proposed approach is validated by both simulation and experimentation.

Distributed MPC-Based Secondary Control for Energy Storage Systems in a DC Microgrid

In this paper, a novel distributed model predictive control (DMPC) strategy based on voltage observer for multiple energy storage systems (ESs) is firstly proposed to achieve a tradeoff between voltage regulation and power sharing. In order to reduce the impact of communication delay on voltage observer, an improved DMPC consensus algorithm is proposed. This scheme improves the robustness of the system to the delay. Besides, a small-signal dynamic model of a DC microgrid with the improved DMPC controllers is established to analyze its dynamic performance. The time-domain simulation results are presented to verify that, under the constraints of the DC bus voltage, a flexible trade-off between voltage regulation and power distribution can be achieved. Besides, the communication delay problems can be reduced.