Distributed Communication Research Articles

A Lyapunov Approach to Consensus of Linear Multi-Agent Systems with Infinite Distributed Communication Delays

This paper considers the leaderless consensus problem of linear time-invariant multi-agent systems with infinite distributed communication delays. A novel distributed low gain controller is proposed based on the solution to a parametric algebraic Riccati equation. It is shown via the newly developed Lyapunov-like method that not only the consensus of linear time-invariant multi-agent systems can be achieved exponentially under some mild assumptions but also an estimate of the exponential convergence rate of consensus is given in this work. The Lyapunov-like method is also extended to handle a special case of linear time-varying multi-agent systems. In addition, the obtained results include the results on the leaderless consensus of linear multi-agent systems with bounded distributed communication delays as special cases. To the best of our knowledge, this is the first work that develops the Lyapunov-like method for the leaderless consensus problems of both time-invariant and time-varying linear multi-agent systems with infinite distributed communication delays. Finally, a numerical example is presented to illustrate the effectiveness of the proposed controller.

Distributed Fractional-Order Intelligent Adaptive Fault-Tolerant Formation-Containment Control of Two-Layer Networked Unmanned Airships for Safe Observation of a Smart City.

This article investigates a distributed fractional-order fault-tolerant formation-containment control (FOFTFCC) scheme for networked unmanned airships (UAs) to achieve safe observation of a smart city. In the proposed control method, an interval type-2 fuzzy neural network (IT2FNN) is first developed for each UA to approximate the unknown term associated with the loss-of-effectiveness faults in the distributed error dynamics, and then a disturbance observer (DO) is proposed to compensate for the approximation error and bias fault encountered by each UA, such that the composite learning strategy composed of the IT2FNN and the DO is obtained for each UA. Moreover, fractional-order (FO) calculus is incorporated into the control scheme to provide an extra degree of freedom for the parameter adjustments. The salient feature of the proposed control scheme is that the composite learning algorithm and FO calculus are integrated to achieve a satisfactory fault-tolerant formation-containment control performance even when a portion of leader/follower UAs is subjected to the actuator faults in a distributed communication network. Furthermore, it is shown by Lyapunov stability analysis that all leader UAs can track the virtual leader UA with time-varying offset vectors, and all follower UAs can converge into the convex hull spanned by the leader UAs. Finally, comparative hardware-in-the-loop (HIL) experimental results are presented to show the effectiveness and superiority of the proposed method.

Trusted and Secure Blockchain-Based Architecture for Internet-of-Medical-Things

The Internet of Medical Things (IoMT) global market has grown and developed significantly in recent years, and the number of IoMT devices is increasing every year. IoMT systems are now very popular and have become part of our everyday life. However, such systems should be properly protected to preventing unauthorized access to the devices. One of the most popular security methods that additionally relies on real-time communication is Blockchain. Moreover, such a technique can be supported by the Trusted Third Party (TTP), which guarantees data immutability and transparency. The research and industrial community has predicted the proliferation of Blockchain-based IoMT (BIoMT), for providing security, privacy, and effective insurance processing. A connected environment comprises some of the unique features of the IoMT in the form of sensors and devices that capture and measure, recognize and classify, assess risk, notify, make conclusions, and take action. Distributed communication is also unique due to the combination of the fact that the Blockchain cannot be tampered with and the Peer-to-Peer (P2P) technique, especially compared to the traditional cloud-based techniques where the reliance of IoMT systems on the centralized cloud makes it somewhat vulnerable. This paper proposes a Blockchain-based technique oriented on IoMT applications with a focus on maintaining Confidentiality, Integrity, and Availability (the CIA triad) of data communication in the system. The proposed solution is oriented toward trusted and secure real-time communication. The presented method is illustrated by an example of a cloud-based hospital application. Finally, the security aspects of the proposed approach are studied and analyzed in detail.

A distributed VSG control method for a battery energy storage system with a cascaded H-bridge in a grid-connected mode

With the high penetration of renewable energy, new challenges, such as power fluctuation suppression and inertial support capability, have arisen in the power sector. Battery energy storage systems play an essential role in renewable energy integration. In this paper, a distributed virtual synchronous generator (VSG) control method for a battery energy storage system (BESS) with a cascaded H-bridge converter in a grid-connected mode is proposed. The VSG is developed without communication dependence, and state-of-charge (SOC) balancing control is achieved using the distributed average algorithm. Owing to the low varying speed of SOC, the bandwidth of the distributed communication networks is extremely slow, which decreases the cost. Therefore, the proposed method can simultaneously provide inertial support and accurate SOC balancing. The stability is also proved using root locus analysis. Finally, simulations under different conditions are carried out to verify the effectiveness of the proposed method.

Historical material of cf. Thoracosaurus from the Maastrichtian of Denmark provides new insight into the K/Pg distribution of Crocodylia

Crocodylia are one of the distinctive groups that survived the K/Pg mass extinction event. New material from Upper Cretaceous–lower Palaeogene deposits is therefore important to understanding shifts in crocodylian distribution and ecology. This paper describes a fragmentary mandible of a marine crocodylian, from the lower Maastrichtian (Upper Cretaceous) of Møns Klint (Denmark). The specimen is referred to cf. Thoracosaurus (Gavialoidea). Although the material was collected in 1968, it has not yet been formally described. However, the specimen warrants further attention, given its palaeoecological and palaeobiogeographical significance. For instance, the Møns Klint “Thoracosaurus” is an indication of increased competition between large piscivores, and of added predation pressure on fish and cephalopod communities. This gavialoid therefore provides new insight into predator-prey interactions in the Danish Chalk palaeoenvironment. Regarding crocodylian distribution, the Møns Klint specimen represents the oldest European gavialoid record, with all other material deriving from uppermost Maastrichtian and Danian deposits. This indicates that Gavialoidea were present in the European “Chalk Sea” throughout the Maastrichtian, rather than being latest Maastrichtian arrivals. Furthermore, the Møns Klint “Thoracosaurus” represents one of few lower Maastrichtian gavialoids worldwide, the other two being from Mississippi and New Jersey (USA). The specimen thus extends the palaeogeographical range of lower Maastrichtian gavialoids across the proto-Atlantic. This reveals transatlantic distribution of Gavialoidea dating back to the earliest Maastrichtian, providing further evidence for distributional communication between marine vertebrate faunas of North America and Europe. These factors make the Møns Klint “Thoracosaurus” particularly valuable to understanding the distribution of K/Pg Crocodylia.

Personas, the Pandemic, and Inclusive, Synthetic, Smart City Planning

In the era of COVID-19 planners, and more broadly, city administrators and policy makers, have learned to cope with the accelerated pace of change, the broad band of uncertainty, and the need for rapid decision-making strategies. This, in the context of ever more diverse communities and greater reliance on technology as an effective response to the social and public health challenges of the pandemic. “Smart” cities harness distributed communication and service delivery technologies to enhance the quality of urban life. The voices of citizens from marginalized and under-served populations, such as older adults and people with disabilities, are vital to the development of inclusive smart cities. In this paper expanding an inclusive policy design approach is proposed that uses ‘personas’ to actively engage those citizens.

A Synchronous Distributed Communication and Control System for SiC-Based Modular Impedance Measurement Units

Single-phase modular impedance measurement unit (IMU) is a promising solution to power system stability analysis. Yet, existing designs only have modularity at the power-stage level other than the control-platform level, which restricts the scalability of modular IMUs. As such, this article proposes a distributed communication and control system (DCCS) for high-frequency large-scale modular IMUs with tight synchronization and low latency to enhance the controller-level modularity and scalability. The new architecture is realized on a widely adopted DSP+FPGA control platform that can be adapted from most existing centralized control systems (CCSs) of modular converters. In this article, the influence of synchronization accuracy (SA) on converter harmonics under carrier-based PWM is first investigated, followed by the study of communication latency’s impact on the system control frequency. Subsequently, the synchronization method of a combined oversampling clock and data recovery (CDR) plus precision time protocol (PTP) method is presented. Furthermore, a communication protocol to maximize control frequencies and a system-level control strategy are elaborated. Finally, controller- and converter-level experimental results are demonstrated on a 520-V, 20-A, SiC-MOSFET-based IMU prototype at 120-kHz equivalent switching frequency, achieving a well-performed ±12.5-ns SA and 60-kHz control frequency.

Biomimetic Chromotropic Photonic‐Ionic Skin with Robust Resilience, Adhesion, and Stability

AbstractThe growing interest in mimicry of biological skins greatly promotes the birth of high‐performance artificial skins. Chameleon skins can actively transform environmental information into bioelectrical and color‐change signals simultaneously through manipulating ion transduction and photonic nanostructures. Here, inspired by chameleon skins, a novel biomimetic chromotropic photonic‐ionic skin (PI‐skin) capable of outputting synergistic electrical and optical signals under strain with robust adhesion, stability, and resilience is ingeniously constructed. The PI‐skin exhibits sensitive structural color change synchronized with electrical response via adjusting the lattice spacing of the photonic crystal (mechanochromic sensitivity: 1.89 nm per %, Δλ > 150 nm). Notably, the polyzwitterionic network provides abundant electrostatic interactions, endowing the PI‐skin with excellent adhesion, environmental tolerance, and outstanding mechanical stability (>10 000 continuous cycles). Meanwhile, the high loading of ionic liquid (IL) weakens the electrostatic interaction between the polyzwitterionic molecular chains, leading to high resilience. The PI‐skin is finally applied to construct a visually interactive wearable device, realizing precise human motion monitoring, remote communication, and visual localization of pressure distribution. This work not only expands design ideas for the construction of advanced biomimetic I‐skins but also provides a general optical platform for high‐level visual interactive devices and smart wearable electronics.

Event-Triggered Dissipative Tracking Control of Networked Control Systems With Distributed Communication Delay

This article presents the design of an event-trigger-based networked robust dissipative tracking control systems. An event-triggered mechanism (ETM) is proposed by introducing the probability density distribution of communication delay. Thus, it can yield less conservative results. The tracking error system is transferred by a distributed communication delay system wherein the delay probability density is viewed as the kernel of the distributed delay. The threshold of the proposed ETM is designed as a dynamic parameter to adapt the transmission of the control signal. By applying the Lyapunov method, sufficient conditions are achieved to ensure the stability of the tracking error system with strictly dissipative performance, which includes <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance and passive performance. Based on the dissipativity analysis condition, a co-design method with both tracking control and the ETM is derived in a united framework. Experiments on networked dc motor tracking system are provided to show the effectiveness of the presented method.

Vulnerability Identification and Remediation of FDI Attacks in Islanded DC Microgrids Using Multiagent Reinforcement Learning

This article proposes a novel approach to uncover deficiencies of the existing cyber-attack detection schemes and thereby to serve as a foundation for establishing more reliable cybersecure solutions, with particular application in dc microgrids. For this purpose, a multiagent deep reinforcement learning (RL)-based algorithm is proposed to automatically discover the vulnerable spots in the conventional index-based cyberattack detection schemes and automatically generate coordinated stealthy destabilizing false data injection (FDI) attacks on cyber-protected islanded dc microgrids. To enable a continuous action space for the trained RL agents and enhance the algorithm’s precision and convergence rate, deep deterministic policy gradient is incorporated. Using this approach, susceptibility of a state-of-the-art detection scheme to several different coordinated FDI attacks on the distributed communication links is identified. The proposed algorithm is also enhanced with a sniffing feature to enable maintaining the stealthy attacks even under the sudden disconnection of any of the compromised links. To address the discovered deficiencies within the index-based detection scheme, a complementary multiagent RL detection algorithm using deep <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Q$</tex-math></inline-formula> -network algorithm is integrated, which provides a more reliable overall identification performance. Taking into account the communication delays and load changes, the effectiveness of the proposed algorithm is verified by the experimental tests.

A hierarchical control scheme with bi-level communication networks for the interconnected DC microgrids cluster

This paper proposes a hierarchical control scheme based on distributed alternating direction method of multipliers (ADMM) for the interconnected DC microgrids cluster. This scheme is fully distributed and consists of three coordinated control levels through bi-level distributed communication networks. The constraints of the economic dispatch problem are decoupled for tertiary control and decomposed into global and local optimization problems using the ADMM framework. To realize parallel computing of ADMM, we designed a fast second-order distributed average consensus algorithm to estimate the global average exchanged value and the average output power of a single microgrid, thus removing the coupling within the microgrids cluster and individual microgrid. Considering the voltage deviation caused by the traditional droop control, voltage control without droop based on the distributed algorithm is proposed to realize voltage restoration and power distribution among dispatchable generators for individual microgrid, combined with traditional primary and secondary control. Numerical simulations of an off-grid microgrids cluster are designed to validate the effectiveness of the proposed control method. Results show that the proposed hierarchical control scheme can ensure the independence and privacy of information, which is beneficial to solve technical and economic challenges brought by centralized optimization. In addition, the proposed algorithm can be applied to more realistic scenarios, such as conditions for time-varying loads and cost functions.

Optimizing Multi-Objective Federated Learning on Non-IID Data with Improved NSGA-III and Hierarchical Clustering

Federated learning (FL) can tackle the problem of data silos of asymmetric information and privacy leakage; however, it still has shortcomings, such as data heterogeneity, high communication cost and uneven distribution of performance. To overcome these issues and achieve parameter optimization of FL on non-Independent Identically Distributed (non-IID) data, a multi-objective FL parameter optimization method based on hierarchical clustering and the third-generation non-dominated sorted genetic algorithm III (NSGA-III) algorithm is proposed, which aims to simultaneously minimize the global model error rate, global model accuracy distribution variance and communication cost. The introduction of a hierarchical clustering algorithm on non-IID data can accelerate convergence so that FL can employ an evolutionary algorithm with a low FL client participation ratio, reducing the overall communication cost of the NSGA-III algorithm. Meanwhile, the NSGA-III algorithm, with fast greedy initialization and a strategy of discarding low-quality individuals (named NSGA-III-FD), is proposed to improve the convergence efficiency and the quality of Pareto-optimal solutions. Under two non-IID data settings, the CNN experiments on both MNIST and CIFAR-10 datasets show that our approach can obtain better Pareto-optimal solutions than classical evolutionary algorithms, and the selected solutions with an optimized model can achieve better multi-objective equilibrium than the standard federated averaging (FedAvg) algorithm and the Clustering-based FedAvg algorithm.

Distributed Nash Equilibrium Computation With Uncertain Dynamics and Disturbances

Nash equilibrium computation problems under distributed communication scenarios are addressed in this paper. In particular, the players, including first- and second-order ones, are considered to be affected by unknown disturbances and dynamics. To accommodate this problem, the followings need to be simultaneously achieved: (1) Distributed estimation of unknown information needed for optimizing the players’ objective functions; (2) The optimization of the players’ objective functions; and (3) Dynamics stabilization for the players, especially for the accommodation of unknown disturbances and dynamics. Based on first-order low-pass filters, an unknown dynamics estimator is established (for the estimation of unknown dynamics and disturbances), by which distributed computing methods are constructed by further employing gradient-like optimization components (for optimizing the players’ objective functions) and consensus components (for distributed action estimation). The presented analytical investigation shows that the players’ actions and velocities (for second-order players) can converge into a small ball around the Nash equilibrium and zero respectively by choosing the control parameters properly according to the given rules. Moreover, the proposed algorithm is adapted to address connectivity control of mobile sensors. Numerical verification is provided by utilizing KUKA YouBot vehicles in V-REP.

The use of computer enhanced education: twenty years of dashed hopes

The purpose of this article is to present conditions implied in the use of Learning Management Systems (LMS), at the University of Borås (UB), Sweden, specifically in 2004, 2009, 2010, and 2018, highlighting patterns that characterize the routines adopted by the teachers. Utilizing quantitative and qualitative approaches, the exploratory research included the analysis of courses in area of STEM (Science, Technology, Engineering, and Mathematics). In addition to a general analysis of the respective courses, a questionnaire was applied to 76 professors and 926 students from the mentioned courses. The pattern of use is analyzed by means of classification of tools in four groups; distribution tools, communication tools, interaction tools, and course management tools. The results confirm that LMS is widely utilized to distribute documents to students, while the tools facilitating interaction and collaboration are used sparingly and this pattern is consistent over time. Despite an increase in the total use of LMS, there is no increase in the use of digital tools for interaction in Higher Education, which indicates the importance of promoting a wide use of collaborative methods and of encouraging interaction.

Statistical Model Checking for Stochastic and Hybrid Autonomous Driving Based on Spatio-Clock Constraints

Autonomous driving vehicles are a kind of typical cyber-physical systems integrating complex interactions between hardware and software components such as collaborative computation, distributed communication, and spatio-clock synchronous control with surrounding traffic environment. They can percept the environment, communicate with surroundings, and react fast enough to control independently. The purpose of autonomous driving emergence is to improve driving safety, reduce environmental pollution, and ease the traffic congestion. However, new features with surrounding open and dynamic environment make systems design and verification becoming more and more complex than ever, such as stochastic communication delay, hardware spontaneous failure distribution, and natively hybrid behaviors described by ordinary differential equations. Spatial and time collision avoidance remains crucial obstacles on the path to becoming ubiquitous and dependable. In this paper, we adopt statistical model checking (SMC) to enlighten possible hazards affected by stochastic and hybrid features in the design phase of autonomous driving systems. In order to provide safety and accountability, we first propose a dedicated multi-lane spatio-clock stochastic specification language (MLSCL) to describe safety invariants and guards in domain-specific autonomous driving systems. Then, we present the semantic mapping rules between MLSCL and UPPAAL SMC models, and design the spatio-clock stochastic and hybrid automata based on MLSCL in order to model inherently stochastic and hybrid behaviors. Finally, we present an illustrative lane-change case study to verify spatio-clock stochastic and hybrid-related properties adopting SMC, and demonstrate the effectiveness of our proposed approach.

Distributed Cooperative Output Regulation of Linear Heterogeneous Multiagent Systems

In this paper, the output regulation problem of fully distributed linear heterogeneous multi-agent systems via event-triggered communication is investigated. A novel information acquisition scheme is proposed, which can effectively save the computing resources of the controller. The time-invariant matrix S is obtained directly through completely distributed communication. Therefore, the computational burden caused by the introduction of matrix observer is reduced. At the same time, to save communication resources, this paper adopts a communication scheme and designs a Zeno-free event-triggered mechanism for each agent. The trigger mechanism in this paper can avoid the continuous monitoring of the system state, and does not need to supplement the self-triggering algorithm. In addition, the control strategy designed in this paper is fully distributed with fixed parameters, and the use of global information can be avoided without using dynamic parameters in the controller. Finally, a numerical example is given to verify the effectiveness of the proposed method.

Supporting Remote Experimentation Through Computer-Mediated Communication

With the emergence of COVID-19 and the resultant reduction in direct personal contact, we were faced with a novel challenge of how to conduct studies that involved both semi-structured elicitation of detailed cognitive information and the evaluation of software interfaces and algorithms. We leveraged distributed communication technologies to support data collection across three separate human-computer interaction studies. We describe these studies in terms of specific computer-mediated communication methods and features and how we used them. We also present lessons learned, potential risks and detriments of using such approaches, (e.g., connectivity dependence, reduced ability to observe non-verbal cues, and diminished interpersonal interaction), along with how the research community can compensate for the shortcomings of distributed data collection in human-centered research.

Microgrid’s multi-VSGs cooperative control method based on distributed communication

Microgrid is a group of interconnected Distributed Generators (DGs) and loads. As an application of renewable energy, microgrid began to enter people’s vision. The technology of Virtual Synchronous Generator (VSG) is becoming a research hotspot owing to it can supply inertia for distributed generation system. For the oscillation problem in microgrid after using VSG technology, this paper theoretically analyzes the variation in output frequency and power of parallel VSGs after system load fluctuation, and proposes a cooperative control method of multi-VSGs. Through distributed communication network, this method improves the output control of each VSG. In the transient process, applied method alleviates the uneven distribution in the active power of the microgrid, while reducing the difference in the output frequency of each VSG, therefore, it can significantly restrain the oscillation and ameliorate the dynamic characteristics of microgrid. A simulation model is established to prove the validity and advantage of this method at the end of this paper.

Research on Zoning, Optimization, Stability, and Nonlinear Control of Wireless Network in Power Grid Communication

To explore the partition optimization and stability of telecommunication network under nonlinear control, a routing optimization algorithm for power control of distribution communication network is proposed, which is based on the Ad-hoc On-demand Distance Vector (AODV) routing optimization algorithm, based on the energy consumption model of wireless sensor network, the optimal routing mechanism for power control is constructed, and the optimal routing mechanism is used to select the route with low energy consumption to solve the problem of energy limitation of wireless sensor nodes. This paper aims at the network routing selection problem in the terminal information collection of the distribution network and designs the routing optimization algorithm of the wireless sensor network. Experimental results show that the model accuracy of the optimized model is 99.8%, the average residual error of the model is about 5.5[Formula: see text]nm, the model accuracy meets the requirements, and the method is effective. According to the confidence interval prediction results of wireless communication link reliability, a node power control system structure of wireless sensor network is proposed, and an optimal control algorithm of communication link quality and reliability of microgrid wireless sensor network based on fuzzy control is studied.

Adaptation to Unknown Leader Velocity in Vector-Field UAV Formation

This article presents a new adaptive method for formation control of unmanned aerial vehicles (UAVs) with limited leader information and communication. We study a formation control protocol in the framework of vector-field guidance where the leader can communicate its position and orientation but not its velocity. A practical motivation for this scenario is the so-called congestion-aware control, in which tradeoffs between the density of unmanned vehicles and communication interference caused by many communicating vehicles arise: these tradeoffs may require to reduce the communication load to avoid interference. To compensate for the lack of knowledge of the leader velocity, each UAV makes use of a local estimation mechanism. The resulting method is an adaptive control method, whose stability can be established using Lyapunov stability. We show that the method can be extended to a distributed communication setting with a few neighboring UAVs in place of the leader. Extensive simulations with different formation shapes (Y, V, and T formation) show that the proposed adaptation mechanism effectively achieves the formation despite the unknown leader velocity. The proposed mechanism has a very similar performance to the ideal case when the leader velocity is perfectly known, and outperforms all the nonadaptive cases in which the followers have an incorrect knowledge of the leader velocity.