Intermittent Communication Research Articles

Pointwise Exponential Stability of State Consensus With Intermittent Communication

Pointwise Exponential Stability of State Consensus With Intermittent Communication

Fuzzy Adaptive Event-Triggered Consensus Control for Nonlinear Multiagent Systems Under Jointly Connected Switching Networks.

This article studies the fuzzy adaptive event-triggered (ET) consensus control issue of nonlinear multiagent systems (NMASs) under jointly connected switching networks. Since the leader and its high-order derivatives are unknown under jointly connected switching networks, a novel distributed ET reference generator equipped with an ET mechanism is constructed to estimate them. Meanwhile, the continuous information transmission among agents is avoided and the network channel utilization is optimized. Subsequently, fuzzy logic systems (FLSs) are employed to approximate unknown dynamics, and a fuzzy adaptive ET consensus control algorithm only using intermittent communication is designed by backstepping control methodology. It is demonstrated that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB), with the tracking errors converging to a small neighborhood around zero. Finally, we apply the developed fuzzy adaptive ET consensus control algorithm to unmanned surface vehicles (USVs), and the simulation results verify the effectiveness of the proposed ET consensus control algorithm.

Testing the limits of SPDM: Authentication of intermittently connected devices

The Security Protocol and Data Model (SPDM) is an open standard for authentication, attestation, and key exchange among hardware units, such as CPUs and peripheral components. In principle, SPDM was designed to operate over a somewhat stable communication channel, meaning that connection losses usually require the re-execution of the entire protocol. This puts into question SPDM’s suitability for battery-powered devices, which may keep only intermittent communications aiming to save energy. To address this question, we evaluate different authentication approaches that build upon and extend SPDM’s native key bootstrapping capabilities to handle intermittent authentication. In particular, we show that the combination of SPDM and a Time-based One-Time Password (TOTP) protocol is a promising solution for this scenario. We analyze the performance of the proposed authentication schemes using a proof-of-concept virtual device. The TOTP-based scheme was shown to be the fastest, the reconnection step being at least twice and up to 900× faster than possible straightforward applications of SPDM. Also, our scheme requires less memory to operate. Finally, we discuss the possibility of integrating intermittent authentication capabilities into the SPDM standard itself.

Finite-Time Hierarchical Containment Control of Heterogeneous Multi-Agent Systems With Intermittent Communication

Finite-Time Hierarchical Containment Control of Heterogeneous Multi-Agent Systems With Intermittent Communication

Zero-Sum-Game-Based Distributed Fuzzy Adaptive Self-Triggered Control of Swarm UAVs Under Intermittent Communication and DoS Attacks

Zero-Sum-Game-Based Distributed Fuzzy Adaptive Self-Triggered Control of Swarm UAVs Under Intermittent Communication and DoS Attacks

Finite-time hybrid impulsive formation tracking control of multi-agent systems via aperiodic intermittent communication

This article studies the problem of formation tracking control in multi-agent systems, achieved in finite time, under challenging conditions such as strong nonlinearity, aperiodic intermittent communication, and time-delay effects, all within a hybrid impulsive framework. The impulses are categorized as either stabilizing control impulses or disruptive impulses. Furthermore, by integrating Lyapunov-based stability theory, graph theory, and the linear matrix inequality (LMI) method, new stability criteria are established. These criteria ensure finite-time intermittent formation tracking while considering weak Lyapunov inequality conditions, intermittent communication rates, and time-varying gain strengths. Additionally, the approach manages an indefinite number of impulsive moments and adjusts the control domain’s width based on the average impulsive interval and state-dependent control width. Numerical simulations are provided to validate the applicability and effectiveness of the proposed formation tracking control protocols.

Event-triggered fixed-time distributed observers for general linear systems

This paper delves into the implementation of a distributed fixed-time state estimation approach for linear systems, utilizing an event-triggered strategy. Particularly, the output data from the linear systems are strategically distributed across various observers. A novel fixed-time distributed observer is proposed to reconstruct full states of the linear system cooperatively with the observer error converges to zero within fixed time. Based on the event-triggered strategy, the communication times among observers are reduced by intermittent communication. Simultaneously, Zeno-behavior is ruled out completely. Finally, the proposed results are verified by a simulation example.

Strong Non-Zeno Mixed Adaptive Dynamic Event-Triggered Control for Distributed Consensus.

This article studies the distributed adaptive event-triggered consensus control problem of linear multiagent systems. A strong non-Zeno mixed adaptive dynamic event-triggering scheme is proposed, which guarantees a strictly positive minimum interevent time (MIET) between any two consecutive events. A model-based event-triggered fully distributed adaptive control law is presented without using prior global information about the communication topology. Moreover, a hybrid system model is constructed to facilitate the stability analysis of the closed-loop system. It is shown that the proposed control strategy can achieve asymptotic consensus of all agents via intermittent communication in a fully distributed way, while guaranteeing the strictly positive MIET property. Finally, the effectiveness of the designed control method is illustrated by a simulation example.

H ∞ consensus control via intermittent communication for nonlinear multi-agent systems with unknown parameters and external disturbances

The consensus control problem is investigated for time-delayed nonlinear leader-following multi-agent systems, in which the unknown parameters and external disturbances are considered. Instead of using only one control method, a control scheme combining periodically intermittent control with H ∞ performance is employed. By manipulating the algebraic graph theory and constructing appropriate Lyapunov–Krasovskii functionals, sufficient solutions assuring the exponential H ∞ consensus of the considered systems are established in the form of linear matrix inequalities. The communication graph among the followers is directed, which removes the restrictions on undirected graph or balanced graph in the literature. Simulation analyses are finally presented to verify the theoretical results.

Hybrid Adaptive Event-Triggered Consensus Control with Intermittent Communication and Control Updating

Hybrid Adaptive Event-Triggered Consensus Control with Intermittent Communication and Control Updating

Scaled consensus of second-order nonlinear multi-agent systems with fully distributed adaptive aperiodically intermittent communication: A non-reduced order approach

Scaled consensus of second-order nonlinear multi-agent systems with fully distributed adaptive aperiodically intermittent communication: A non-reduced order approach

Bipartite finite-time consensus of multi-agent systems with intermittent communication via event-triggered impulsive control

This paper concentrates on the bipartite finite-time consensus (BFTC) problem of nonlinear multi-agent systems (MASs) under intermittent communication via event-triggered impulsive control. First, a finite-time consensus (FTC) protocol with an event-triggered mechanism is developed for the MASs with nonlinear dynamics to save limited resources. Then, an impulsive control scheme is introduced to the designed algorithm to further improve the control performance. Based on the structurally balanced graph theory, both antagonistic and cooperative interactions are discussed in this article. Regarding whether the MASs have encountered intermittent communication, sufficient conditions are provided for achieving consensus of the MASs by using the Lyapunov theory and inductive methods. Moreover, the Zeno behavior is excluded. Finally, numerical simulations are given to validate the effectiveness of the algorithm. The result shows that the designed event-triggered BFTC control protocol with an impulsive strategy has a faster convergence rate than that without an impulsive strategy.

Resilient Virtual Coupling Control of Automatic Train Convoys With Intermittent Communications

Resilient Virtual Coupling Control of Automatic Train Convoys With Intermittent Communications

Finite-time tracking control of heterogeneous multi-AUV systems with partial measurements and intermittent communication

Finite-time tracking control of heterogeneous multi-AUV systems with partial measurements and intermittent communication

Distributed event-triggered estimation for dynamic average consensus: A perturbation-injected privacy-preservation scheme

Previous studies on the distributed estimation problem for dynamic average consensus of multi-agent networks are usually based on the assumption that each agent continuously and honestly shares information with its neighbors. To relax this assumption, this paper focuses on the distributed event-triggered private estimation problem. By injecting random perturbations into the original reference signal, an adaptive robust distributed privacy-preserving event-triggered estimation algorithm is proposed. With the proposed algorithm, the convergence of the estimation error is guaranteed under intermittent communication, while protecting the private reference signal information from disclosure. To determine the timing for communication, an adaptive distributed dynamic triggering mechanism with a dynamically updated internal triggering variable is designed. In addition, a dynamically updated adaptive gain instead of a static gain is employed in the estimation algorithm and triggering mechanism to eliminate the dependence on some global information. Finally, numerical simulation results are presented to illustrate the validity of the theoretical results.

Output-Feedback Multiagent Consensus With Intermittent Communication on Directed Graphs

Output-Feedback Multiagent Consensus With Intermittent Communication on Directed Graphs

Distributed Cooperative Optimization for Nonlinear Heterogeneous MASs Under Intermittent Communication

Distributed Cooperative Optimization for Nonlinear Heterogeneous MASs Under Intermittent Communication

Task offloading optimization in mobile edge computing under uncertain processing cycles and intermittent communications

Mobile edge computing (MEC) has emerged as a promising solution for addressing the growing computational demands by enabling cloud computing capabilities at the network edge. However, existing MEC models typically make assumptions of known processing cycles and uninterrupted communications, which are not practical in real-world scenarios. This paper aims to tackle the challenges posed by uncertainties and intermittent communications in MEC systems in the context of task offloading. We first derive a closed-form expression for the average offloading success probability in a device-to-device (D2D) assisted MEC system. This expression accurately accounts for uncertain computation processing cycles and intermittent communications. Then, we formulate the task offloading maximization problem (TOMP) and prove its NP-hardness. For problem-solving, we propose two algorithms tailored to different scenarios. In instances exhibiting a uniform structure, we introduce a task scheduling algorithm based on dynamic programming (TSDP). When dealing with general scenarios, we reformulate the problem and propose a repeated matching algorithm (RMA). We use Monte Carlo simulations to validate the closed-form expression. The results demonstrate that gap between them is less than 0.55%, confirming the accuracy of the closed-form expression. Furthermore, the proposed algorithms outperform other algorithms by performance comparison.

Internal model observer-based distributed moving-target-fencing control of multiple underactuated marine surface vehicles with intermittent communications

This study addresses the moving target fencing (MTF) control problem of multiple underactuated marine surface vehicles (MSVs) with varying intermittent communication under a directed graph. A distributed internal model observer (DIMO) was proposed to estimate the target trajectory for each vehicle with intermittent communication. Combined with this observer, an MTF control scheme was developed to cooperatively fence a moving target in a convex hull that quasi-asymptotically rotates equally around the target at the centre. Collision avoidance was guaranteed simultaneously. Furthermore, the stability of the proposed control scheme was analysed using the Lyapunov theory. Finally, numerical examples and experiments are conducted to demonstrate the validity and stability of the proposed control approach.

Multiagent Cooperative Search Learning With Intermittent Communication

Multiagent Cooperative Search Learning With Intermittent Communication