Event-Triggered Resilient Consensus of Networked Euler–Lagrange Systems Under Byzantine Attacks

Resilient consensus with switching networks and heterogeneous agents

Although quite a few results on resilient consensus of multi-agent systems with malicious agents and fixed topology have been reported in the literature, we lack any known results on such a problem for multi-agent systems with time-varying topologies. Herein, we study the resilient consensus problem of time-varying networked systems in the presence of misbehaving nodes. A novel concept of joint ( r, s) -robustness is firstly proposed to characterize the robustness of the time-varying topologies. It is further revealed that the resilient consensus of multi-agent systems under F-total malicious network can be reached by the Weighted Mean-Subsequence-Reduced algorithm if and only if the time-varying graph is jointly ( F+1, F+1) -robust. Numerical simulations are finally performed to verify the effectiveness of the analytical results.

Network-based H∞ control for T–S fuzzy systems with an adaptive event-triggered communication scheme

This paper considers a delay tolerant network consisting of nodes equipped with sensors, some of them producing outliers. A distributed faulty node detection (DFD) algorithm, whose aim is to help each node in estimating the status of its sensors, has been proposed recently by the authors. The aim of this paper is to analyze the robustness of the DFD algorithm to the presence of misbehaving nodes performing Byzantine attacks. Two types of attacks are considered and analyzed, each trying to mislead the other nodes in the estimation of the status of their sensors. This provides insights on the way the parameters of the DFD algorithm should be adapted to minimize the impact of misbehaving nodes. Theoretical results are illustrated with simulations considering nodes with random displacements, as well as traces of node inter-contact times from real databases.

Cognitive radio (CR) has emerged as a solution to the problem of spectrum scarcity as it exploits the transmission opportunities in the under-utilized spectrum bands of primary users. Collaborative (or distributed) spectrum sensing has been shown to have various advantages in terms of spectrum utilization and robustness. The data fusion scheme is a key component of collaborative spectrum sensing. In this paper, we analyze the performance limits of collaborative spectrum sensing under Byzantine Attacks where malicious users send false sensing data to the fusion center leading to increased probability of incorrect sensing results. We show that above a certain fraction of Byzantine attackers in the CR network, data fusion scheme becomes completely incapable and no reputation based fusion scheme can achieve any performance gain. We present optimal attacking strategies for given attacking resources and also analyze the possible counter measures at the fusion center (FC).

The parallel distributed detection is studied for mobile wireless sensor networks (MWSNs) in the presence of Byzantine attacks in entirely unknown environment or complicated environment from the perspective of the information theory, where we pay most of our attention toward design, analysis, and evaluation of the attack strategy. In particular, the multihop relay network and the harsh wireless communication condition, e.g., the dynamic and entirely unknown channel, are taken into consideration in our configuration. Second, the conditions that the optimal attacking strategy should satisfy is analyzed and developed under different attacking scenarios. Third, the minimum attacking power is developed for the Byzantines to blind the fusion center (FC). Furthermore, the optimal attacking strategies are developed when no prior information of the system is known for the Byzantines. Finally, the traditional four typical attack strategies are evaluated, and we find that the fraction of Byzantines is the only factor that affects the reliable data fusion when the network size and the attacking strategy are fixed. The extensive simulation is conducted to verify our design, analysis, and evaluation of the attack strategy.

Fixed-time and predefined-time group-bipartite consensus for uncertain networked Euler-Lagrange systems

This paper investigates the distributed leaderless consensus problem of networked Markov jump multi-agent systems with mode-dependent switching topologies. Specifically, a novel mode-dependent sampling and event-triggered communication strategy is proposed to reduce the network burden with less conservatism. Based on model transformation and constructing the mode-dependent Lyapunov-Krasovskii functional, sufficient consensus criteria are first established. Then, the desired event triggering function parameters and the controller gains are designed in terms of linear matrix inequalities (LMIs). In the end, an illustrative example is provided to verify the effectiveness of our proposed consensus method.

In recent years, multi-agent systems have attracted considerable attention, particularly with regard to their security dimensions in presence of Byzantine attacks. However, existing Byzantine-resilient algorithms rely on relatively strong network connectivity conditions, raising the question of whether these requirements can be relaxed while balancing performance trade-offs. To address this, we partition the full state of each agent into multiple blocks and leverage an essentially cyclic rule for each block update, based on which a filter-based block consensus algorithm is proposed. This approach not only relaxes network connectivity requirements but also reduces bandwidth usage per update, making it suitable for a wider range of networks. Theoretical analysis demonstrates that the algorithm achieves linear consensus speed, ensuring fast and robust aggregation among nodes despite Byzantine agents.

This article investigates the event-triggered leader-follower consensus control problem for linear continuous-time multiagent systems (MASs). A new consensus protocol and an event-triggered communication (ETC) strategy based on a closed-loop state estimator are designed. The closed-looped state estimator renders us more accurate state estimations, therefore the triggering times can be decreased while maintaining control performance. We show that the consensus of MASs can be achieved by employing the proposed control scheme. In addition, the Zeno-phenomena can be excluded. As a practical application, our method is successfully applied to the vehicle platoon control. The effectiveness is further verified by simulations conducted on the Prescan platform.

Traditionally, the Byzantine Agreement (BA) problem is studied either in a fully connected network or in a broadcast network. A generalized network model for BA is proposed in this paper. A fully-connected network or a broadcast network is a special case of the new network architecture. Under the new generalized network model, the BA problem is reexamined with the assumption of malicious faults on both processors and transmission medium (TM), as opposed to previous studies which consider malicious faults on processors only. The proposed algorithm uses the minimum number of message exchanges, and can tolerate the maximum number of allowable faulty components to make each healthy processor reach a common agreement for the cases of processor failures, TM failures, or processor/TM failures. The results can also be used to solve the interactive consistency problem and the consensus problem.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Distributed consensus is an important class of distributed algorithms and has attracted great interests in recent years in multi-agent systems, but it introduces a new security issue that adversarial agents may manipulate false information to disrupt the correct operation of consensus process of the whole network. This paper institutes the resilient consensus problem of multi-agent networks under limited communication. The communication channels among the nodes are constrained in which the exchanged information is quantized. The objective is to design a quantized-data based control protocol so that the safe agents can withstand the attackers and acquire an agreement as time goes to infinity. Finally, an example and simulation results are given to illustrate the effectiveness of the algorithm.

In this paper, the problem of consensus for multiagent systems, modeling by Euler-Lagrange equations, is studied with event-triggered communication network. By utilizing a proportional plus damping control scheme, a triggering mechanism is developed so that agents can achieve consensus without continuously exchange their signals. The networked system is demonstrated to be stable with guaranteed consensus performance if the communication topology between agents are undirected and connected. Moreover, a triggering gain is introduced to tune the triggering sensitivity and frequency. The lower bounds of inter-event time for agents are presented so that the Zeno behavior is avoided in the event-triggered control system. The proposed system can reduce network-access-frequency, and stop exchanging output signals when the multi-agent system achieve consensus. Simulations with four Euler-Lagrange agents are illustrated to show the performance and efficiency of the proposed system.

This chapter investigates the problem of stabilization of nonlinear discrete-time networked control systems (NCS) with event-triggering communication scheme in the presence of signal transmission delay. A Takagi–Sugeno (T–S) fuzzy model and parallel-distributed compensation (PDC) scheme are first employed to design a nonlinear fuzzy event-triggered controller for the stabilization of nonlinear discrete-time NCS. The idea of the event-triggering communication scheme (a soft computation algorithm) under consideration is that the current sensor data is transmitted only when the current sensor data and the previously transmitted one satisfy a certain state-dependent trigger condition. By taking the signal transmission delay into consideration and using delay system approach, a T–S fuzzy delay system model is established to describe the nonlinear discrete-time NCSs with event-triggering communication scheme. Attention is focused on the design of fuzzy event-triggered controller which ensures asymptotic stability of the closed-loop fuzzy systems. Linear matrix inequality- (LMI-) based conditions are formulated for the existence of admissible fuzzy event-triggered controller. If these conditions are feasible, a desired fuzzy event-triggered controller can be readily constructed. A nonlinear mass-spring-damper mechanical system is presented to demonstrate the effectiveness of the proposed method.

In this paper, we study the consensus problem of multiple Euler-Lagrange systems subject to limited communication resources and parametric uncertainties. Firstly, an event-triggered communication scheme is proposed to achieve the leaderless consensus problem. With the proposed event-triggered mechanism, the state of each subsystem is transmitted at event instants which are aperiodic and asynchronous with respect to other subsystems. Secondly, we consider the time-delay effects in communication. The consensus analysis of the proposed scheme is based on the small-gain framework. Finally simulation results on a network of robot manipulators are given to illustrate the effectiveness of the proposed control scheme.