Event-based Communication Research Articles

Event-triggered prescribed-time control for a class of uncertain nonlinear systems using finite time-varying gain

This paper addresses the event-triggered prescribed-time control problem for a class of high-order nonlinear systems based on finite time-varying gain. Due to the existence of unknown gain functions and system uncertainties, the resultant control with prescribed-time convergence performance becomes nontrivial. The problem becomes even more complex due to the use of event-based communication instead of continuous communication. To tackle the aforementioned challenges, this paper proposes an event-triggered prescribed-time stabilization approach with the following key steps. Firstly, we establish a new prescribed-time stability lemma to overcome the technical difficulty arising from the prescribed-time controller design, and stability analysis. Secondly, we give the controller design procedure upon using the backstepping technique. Thirdly, we redesign the event-triggering threshold condition based on time-varying functions, which allows the controller terminal jitter to be mitigated and the controller to be implemented straightforwardly in practice. Furthermore, the proposed control scheme avoids Zeno behavior. The numerical simulation confirms the effectiveness of the proposed control scheme.

A Framework for Distributed Estimation With Limited Information and Event-Based Communications

A Framework for Distributed Estimation With Limited Information and Event-Based Communications

Event-Triggered Consensus of Uncertain Euler-Lagrange Multiagent Systems Over Jointly Connected Digraphs.

In this article, a fully distributed event-triggered protocol is proposed to solve the consensus problem of uncertain Euler-Lagrange (EL) multiagent systems (MASs) under jointly connected digraphs. First, distributed event-based reference generators are proposed to generate continuously differentiable reference signals via event-based communication under jointly connected digraphs. Unlike some existing works, only the states of agents rather than virtual internal reference variables need to be transmitted among agents. Second, adaptive controllers are exploited based on the reference generators so that each agent can track the reference signals. The uncertain parameters converge to their real values under an initially exciting (IE) assumption. It is proved that the uncertain EL MAS achieves state consensus asymptotically under the proposed event-triggered protocol composed of the reference generators and the adaptive controllers. A unique feature of the proposed event-triggered protocol is its fully distributed property: the protocol does not depend on global information about the jointly connected digraphs. Meanwhile, a minimum interevent time (MIET) is guaranteed. Finally, two simulations are conducted to show the validity of the proposed protocol.

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Simulation models have been described using different perspectives, or worldviews. In the process interaction world view (PI), every entity is modeled by a sequence of actions describing its life cycle, offering a comprehensive model that groups the events involving each entity. In this paper we describe π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}HyFlow, a formalism for representing hybrid models using a set of communicating processes. This set is dynamic, enabling processes to be created and destroyed at runtime. Processes are encapsulated into π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}HyFlow base models and communicate through shared memory. π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}HyFlow, however, can guarantee modularity by enforcing that models can only communicate by input and output interfaces. π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}HyFlow extends current PI approaches by providing support for HyFlow concepts of sampling and dense (continuous) outputs, in addition to the more traditional event-based communication. Likewise HyFlow, π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}HyFlow is a modeling & simulation formalism driven by expressiveness and performance analysis. We present π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}HyFlow semantics, and several applications to illustrate π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}HyFlow ability to describe a diversity of systems.

Distributed Constrained Optimization for Second-Order Multiagent Systems via Event-Based Communication

Distributed Constrained Optimization for Second-Order Multiagent Systems via Event-Based Communication

Intermittent Fixed-Time Fuzzy Consensus of Nonlinear Multiagent Systems With Unknown Control Directions and Event-Based Communication

Intermittent Fixed-Time Fuzzy Consensus of Nonlinear Multiagent Systems With Unknown Control Directions and Event-Based Communication

Generally Genius: A Generals.io Agent Development and Data Collection Framework

We present an agent development and data collection framework for Generals.io (GIO)--a real-time strategy game with imperfect information in which players attempt to gain control of opponents' starting positions within a 2D grid world. The framework provides event-based communication amongst several modules implemented as microservices, enabling real-time data collection from GIO's streaming data. Its modular design facilitates rapid bot development and testing, while the emphasis on data collection makes it easy to analyze agent performance. We use this framework in a case study of a top-performing GIO agent called Flobot. Our analysis demonstrates that Flobot's performance varies based on its starting position. Based on the analysis performed with our framework, we propose a modification to Flobot's pathfinding algorithm. Statistical tests show that the new algorithm results in a significant reduction in performance variance.

Resilient Synchronization of Networked Lagrangian Systems Over Event-Based Communication With Asynchronous DoS Attacks

A wide range of actual systems can be modeled as Euler- Lagrange dynamics, its inherently complex nonlinearities present additional difficulties in the design of control algorithms. In this paper, the distributed resilient synchronization control problem of networked Euler- Lagrange (E-L) systems under event-based communication with distributed denial-of-service (DoS) attacks is considered. A novel distributed dynamic event-triggered scheme is proposed to schedule the communication source under asynchronous DoS attacks on different channels. Then, a self-triggered scheme is designed to reduce the updating number of the control signals. Under the proposed adaptive control scheme, the asymptotic synchronization of the closed-loop system is guaranteed under DoS attacks. Neither the control strategy nor the dual-terminal event-triggered scheme needs the eigenvalue information of the Laplace matrix. Also, no Zeno behavior occurs under the proposed event-based control and communication framework. Finally, case studies are provided to show the effectiveness of the proposed method.

Design of Event-Triggered Asynchronous H∞ Filter for Switched Systems Using the Sampled-Data Approach

The design of networked switched systems with event-based communication is attractive due to its potential to save bandwidth and energy. However, ensuring the stability and performance of networked systems with event-triggered communication and asynchronous switching is challenging due to their time-varying nature. This paper presents a novel sampled-data approach to design event-triggered asynchronous <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> filters for networked switched systems. Unlike most existing event-based filtering results, which either design the event-triggering scheme only or co-design the event-triggering condition and the filter, we consider that the event-triggering policy is predefined and synthesize the filter. We model the estimation error system as an event-triggered switched system with time delay and non-uniform sampling. By implementing a delay-dependent multiple Lyapunov method, we derive sufficient conditions to ensure the global asymptotic stability of the filtering error system and an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance level. The efficacy of the proposed design technique and the superiority of the filter performance is illustrated by numerical examples and by comparing the performance with a recent result.

On the trade-off between event-based and periodic state estimation under bandwidth constraints

Event-based methods carefully select when to transmit information to enable high-performance control and estimation over resource-constrained communication networks. However, they come at a cost. For instance, event-based communication induces a higher computational load and increases the complexity of the scheduling problem. Thus, in some cases, allocating available slots to agents periodically in circular order may be superior. In this article, we discuss, for a specific example, when the additional complexity of event-based methods is beneficial. We evaluate our analysis in a synthetical example and on 20 simulated cart-pole systems.

METHODS TO SYNCHRONIZE DATA IN A MICROSERVICE ARCHITECTURE

This article discusses the problem of data synchronization methods using microservice architecture. Microservices is a popular and widespread software architecture today. The article reviews three main ways of interaction of microservices. They are event-based communication, interaction through direct HTTP requests and messaging, and also highlights and analyzes their advantages and disadvantages. The main purpose of the article is to analyze and make offer of the optimal option for solving the problem of synchronizing interacting microservices in real time. The optimal solution involves using the Apache Kafka message broker. It publishes data streams and subscriptions to them, as well as stores and processes them. Mathematical modeling of the proposed data synchronization method was described by constructing its state macine, as well as a system of canonical equations.

Dynamic Quantization Driven Synchronization of Networked Systems Under Event-Triggered Mechanism

This paper focuses on the synchronization control issue of networked systems. Due to the imperfect network environment, continuous or precise transmission is impractical, and intermittent communication scheme under state quantization needs to be considered. First, an easy-to-implement dynamic quantizer, which possesses finite quantization level, is designed to deal with the imprecise information sharing. Next, based on the designed quantizer, a dynamic estimator is introduced to estimate the real-time state information and generate control inputs. An event-based communication scheme is utilized to ensure that the estimate error does not exceed a certain threshold. Then, detailed design of the dynamically quantized controller is given to achieve exact synchronization, and corresponding distributed design is also provided to improve the feasibility. Moreover, some results for practical synchronization are derived. Finally, the validity of our theoretical results is illustrated by two numerical examples.

Distributed Fault-Tolerant Target Tracking Using Event-Based Communication in Internet of Robotic Things

Distributed Fault-Tolerant Target Tracking Using Event-Based Communication in Internet of Robotic Things

Event-Based Communication Strategies for Collaborative Inertial Radio SLAM

Event-based communication strategies for vehicles navigating by aiding their inertial navigation systems (INSs) with terrestrial signals of opportunity (SOPs) are developed. The following problem is considered. Multiple navigating vehicles with access to global navigation satellite system (GNSS) signals are aiding their on-board INSs with GNSS pseudoranges. While navigating, vehicle-mounted receivers draw pseudorange measurements from terrestrial SOPs with unknown emitter positions and unknown and unsynchronized clocks. The vehicles share INS data and SOP pseudoranges to collaboratively estimate the SOPs' states through an extended Kalman filter. After some time, GNSS signals become unavailable, at which point the navigating vehicles use shared INS and SOP information to continue navigating in a collaborative inertial radio simultaneous localization and mapping (CIRSLAM) framework. Two eventbased communication strategies to share this information are developed, where instead of sharing information at a fixedrate when measurements become available, information is only shared whenever any vehicle's position error could violate a userspecified position error threshold with some desired probability. Simulation results are presented demonstrating the tradeoff between localization performance and the accumulated transmitted data when the event-based transmission scheme is employed versus sharing data at the fixed-rate. Experimental results are presented demonstrating two unmanned aerial vehicles (UAVs) navigating in a CIRSLAM framework with SOP pseudoranges drawn from terrestrial cellular towers. The event-based communication scheme reduced the cumulative communicated data by 86.6% compared to a fixed-rate scheme, while maintaining the specified error constraint.

Improving the Performance of Cooperative Platooning With Restricted Message Trigger Thresholds

Cooperative Vehicular Platooning (Co-VP) is one of the most prominent and challenging applications of Intelligent Traffic Systems. To support such vehicular communications, the ETSI ITS G5 standard specifies event-based communication profiles, triggered by kinematic parameters such as speed. The standard defines a set of threshold values for such triggers but no careful assessment in realistic platooning scenarios has been done to confirm the suitability of such values. In this work, we investigate the safety and performance limitations of such parameters in a realistic platooning co-simulation environment. We then propose more conservative threshold values, that we formalize as a new profile, and evaluate their impact in the longitudinal and lateral behaviour of a vehicular platoon as it carries out complex driving scenarios. Furthermore, we analyze the overhead introduced in the network by applying the new threshold values. We conclude that a pro-active message transmission scheme leads to improved platoon performance for highway scenarios, notably an increase greater than 40% in the longitudinal performance of the platoon, while not incurring in a significant network overhead. The obtained results also demonstrated an improved platoon performance for for semi-urban scenarios, including obstacles and curves, where the heading error decreases in 26%, with slight network overhead.

Event-based Communication for decentralized Automation Systems

Event-based Communication for decentralized Automation Systems

A semi-Markovian jumping system approach to secure DPC of nonlinear networked unmanned marine vehicle systems with DoS attack

In this paper, the problem of secure dynamic positioning control (DPC) for a network-based T-S fuzzy unmanned marine vehicle (UMV) systems is addressed. Firstly, a Takagi–Sugeno (T-S) fuzzy system model is adopted to model the nonlinear dynamics of UMV systems. Then, a semi-Markovian jumping system approach is introduced to describe the unknown DoS attack phenomenon. In order to reduce the communication burden, an event-based communication scheme is proposed. By means of the Lyapunov stability analysis method and semi-Markovian jumping system approach, the sufficient conditions are devised such that the closed-loop dynamic positioning system (DPS) is robust stochastically stable. Furthermore, by solving a few LMIs, the controller gain parameters can be derived. Finally, an illustrative example of networked T-S fuzzy UMV system is established to verify the proposed control algorithm.

Adaptive backstepping based consensus tracking of uncertain nonlinear systems with event-triggered communication

This paper investigates the consensus tracking problem for a class of uncertain high-order nonlinear systems with parametric uncertainties and event-triggered communication. Under a directed communication condition, a totally distributed adaptive backstepping based control scheme is presented. Specifically, a decentralized triggering condition is adopted in this paper such that continuous monitoring of neighboring states, as required in some existing results, can be avoided. Besides, to handle the non-differentiability problem of virtual controllers, which arises from the utilization of neighboring states collected only at the triggering instants, the virtual controllers in each recursive step are firstly designed with continuous communication. Then, the partial derivatives of these designed virtual controllers are adopted to construct distributed adaptive consensus controllers for the event based communication case. It is shown that with the presented distributed adaptive consensus control scheme and even-triggered communication mechanism, all the closed-loop signals are uniformly bounded and the output consensus tracking errors will converge to a compact set. Besides, the tracking performance in the mean square sense can be improved by appropriately adjusting design parameters.

Event-based backpropagation can compute exact gradients for spiking neural networks

Spiking neural networks combine analog computation with event-based communication using discrete spikes. While the impressive advances of deep learning are enabled by training non-spiking artificial neural networks using the backpropagation algorithm, applying this algorithm to spiking networks was previously hindered by the existence of discrete spike events and discontinuities. For the first time, this work derives the backpropagation algorithm for a continuous-time spiking neural network and a general loss function by applying the adjoint method together with the proper partial derivative jumps, allowing for backpropagation through discrete spike events without approximations. This algorithm, EventProp, backpropagates errors at spike times in order to compute the exact gradient in an event-based, temporally and spatially sparse fashion. We use gradients computed via EventProp to train networks on the Yin-Yang and MNIST datasets using either a spike time or voltage based loss function and report competitive performance. Our work supports the rigorous study of gradient-based learning algorithms in spiking neural networks and provides insights toward their implementation in novel brain-inspired hardware.

Nonsmooth Resource Allocation of Multiagent Systems With Disturbances: A Proximal Approach

This article aims to solve the nonsmooth resource allocation problem in the presence of a global network resource constraint and local set constraints in the framework of multiagent system optimization. It is assumed that multiagent systems are subject to some external disturbances, and the control inputs of the agents satisfy Lispchitz continuity. These two distinguished features render the existing distributed optimization algorithms, especially the subgradient-based algorithms inapplicable due to the employment of discontinuity of subgradients. To solve such a challenging resource allocation problem, a new kind of continuous-time proximal algorithm is designed with the aid of convex optimization theory and the internal-model technique. The proximal algorithm is further augmented by introducing an event-based communication scheme such that the continuous-time communication among the agents is avoided successfully. The theoretical analysis shows that the multiagent systems under the proposed algorithms can converge to the optimal solution of the considered problem, while the external disturbances are rejected. Besides, the Zeno behavior can be excluded for the proximal algorithm with event-based communication. Finally, the numerical simulations are given to verify the established theoretical results.