Efficient Algorithms for the Consensus Decision Problem

We address the problem of determining if a discrete time switched consensus system converges for any switching sequence and that of determining if it converges for at least one switching sequence. For these two problems, we provide necessary and sufficient conditions that can be checked in singly exponential time. As a side result, we prove the existence of a polynomial time algorithm for the first problem when the system switches between only two subsystems whose corresponding graphs are undirected, a problem that had been suggested to be NP-hard by Blondel and Olshevsky.Comment: Small modifications after comments from reviewer

Time-and event-driven communication process for networked control systems: A survey

Copyright © 2014 Lei Zou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In recent years, theoretical and practical research topics on networked control systems (NCSs) have gained an increasing interest from many researchers in a variety of disciplines owing to the extensive applications of NCSs in practice. In particular, an urgent need has arisen to understand the effects of communication processes on system performances. Sampling and protocol are two fundamental aspects of a communication process which have attracted a great deal of research attention. Most research focus has been on the analysis and control of dynamical behaviors under certain sampling procedures and communication protocols. In this paper, we aim to survey some recent advances on the analysis and synthesis issues of NCSs with different sampling procedures (time-and event-driven sampling) and protocols (static and dynamic protocols). First, these sampling procedures and protocols are introduced in detail according to their engineering backgrounds as well as dynamic natures. Then, the developments of the stabilization, control, and filtering problems are systematically reviewed and discussed in great detail. Finally, we conclude the paper by outlining future research challenges for analysis and synthesis problems of NCSs with different communication processes.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Resilient Cluster Consensus of Multiagent Systems

We investigate the problems of resilient cluster consensus in directed networks under three types of multiagent dynamics, namely, continuous-time multiagent systems, discrete-time multiagent systems, and switched multiagent systems composed of both continuous-time and discrete-time components. Resilient cluster censoring strategies are proposed to ensure cluster consensus against locally bounded Byzantine nodes in a purely distributed manner, where neither the number/identity of Byzantine nodes nor the division of clusters is assumed. We do not require complicated algebraic conditions or any balance conditions over intercluster structures, distinguishing the current work from previous results on cluster consensus problems besides a fortiori the attack-tolerant feature. Sufficient conditions are established in all the three scenarios based on the graph robustness. Furthermore, we solve the heterogenous cluster robustness problems and resilient scaled cluster consensus problems as extensions. The theoretical results are illustrated through numerical examples including the Santa Fe collaboration network

Resilient group consensus in heterogeneously robust networks with hybrid dynamics

This paper studies resilient coordinated control over networks with hybrid dynamics and malicious agents. In a hybrid multi‐agent system, continuous‐time and discrete‐time agents concurrently exist and communicate through local interaction. We introduce the notion of heterogeneous robustness to capture the topological structure and facilitate convergence analysis of hybrid agents over multiple subnetworks, where the exact number and identities of malicious agents are not known. A hybrid resilient strategy is first designed to ensure group consensus of the heterogeneously robust network admitting completely distributed implementation. We then develop a scaled consensus protocol which allows different clusters within each subnetwork, providing further flexibility over the resilient control tasks. Finally, some numerical examples are worked out to illustrate the effectiveness of theoretical results

A resilient continuous-time consensus method using a switching topology

DynamiCITY ( NORTE-01-0145-FEDER-000073 ), funded by NORTE2020/PORTUGAL2020 , through the European Regional Development Fund . Publisher Copyright: © 2022 The Author(s)This paper addresses the design problem of a resilient consensus algorithm for agents with continuous-time dynamics. The main proposal is that by incorporating a switching mechanism selecting the network topology to avoid malicious nodes from communicating, the remaining nodes will converge to a value closer to the original steady-state without the attacker being present. The switching occurs at discrete-time steps where each node evaluates the reputation score of the neighbors and deactivates/ignores edges in the network. We explore the proposed method with illustrative examples ranging from static topologies to dynamic ones, considering directed and undirected graphs, presenting several attacking scenarios that are successfully mitigated with our method. Finally, we compare the best undetectable attacking strategy and the commonly used approach named MSR, highlighting the advantages of our method.publishersversionpublishe

Fully distributed consensus for high-order strict-feedback nonlinear multiagent systems with switched topologies

summary:This paper studies the distributed consensus problem of high-order strict-feedback nonlinear multiagent systems. By employing the adaptive backstepping technique and switched system theory, a novel protocol is proposed for MASs with switched topologies. Global information such as the number of agents and communication topology is not used. In addition, the communication topology between agents can be switched between possible topologies at any time. Based on the Lyapunov function method, the proposed adaptive protocol guarantees the complete consensus of multiagent systems without restricting the dwell time of the switched signal. Finally, two numerical examples are provided to illustrate the effectiveness and advantages of the given protocol

Network Inference from Consensus Dynamics

We consider the problem of identifying the topology of a weighted, undirected network $\mathcal G$ from observing snapshots of multiple independent consensus dynamics. Specifically, we observe the opinion profiles of a group of agents for a set of $M$ independent topics and our goal is to recover the precise relationships between the agents, as specified by the unknown network $\mathcal G$. In order to overcome the under-determinacy of the problem at hand, we leverage concepts from spectral graph theory and convex optimization to unveil the underlying network structure. More precisely, we formulate the network inference problem as a convex optimization that seeks to endow the network with certain desired properties -- such as sparsity -- while being consistent with the spectral information extracted from the observed opinions. This is complemented with theoretical results proving consistency as the number $M$ of topics grows large. We further illustrate our method by numerical experiments, which showcase the effectiveness of the technique in recovering synthetic and real-world networks.Comment: Will be presented at the 2017 IEEE Conference on Decision and Control (CDC

COORDINATION OF LEADER-FOLLOWER MULTI-AGENT SYSTEM WITH TIME-VARYING OBJECTIVE FUNCTION

This thesis aims to introduce a new framework for the distributed control of multi-agent systems with adjustable swarm control objectives. Our goal is twofold: 1) to provide an overview to how time-varying objectives in the control of autonomous systems may be applied to the distributed control of multi-agent systems with variable autonomy level, and 2) to introduce a framework to incorporate the proposed concept to fundamental swarm behaviors such as aggregation and leader tracking. Leader-follower multi-agent systems are considered in this study, and a general form of time-dependent artificial potential function is proposed to describe the varying objectives of the system in the case of complete information exchange. Using Lyapunov methods, the stability and boundedness of the agents\u27 trajectories under single order and higher order dynamics are analyzed. Illustrative numerical simulations are presented to demonstrate the validity of our results. Then, we extend these results for multi-agent systems with limited information exchange and switching communication topology. The first steps of the realization of an experimental framework have been made with the ultimate goal of verifying the simulation results in practice