1,435 research outputs found
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
Consensus Tracking for Multiagent Systems Under Bounded Unknown External Disturbances Using Sliding-PID Control
This paper is devoted to the study of consensus tracking for multiagent systems under unknown but bounded external disturbances. A consensus tracking protocol which is a combination between the conventional PID controller and sliding mode controller named sliding-PID protocol is proposed. The protocol is applied to the consensus tracking of multiagent system under bounded external disturbances where results showed high effectiveness and robustness
Multiplex PI-Control for Consensus in Networks of Heterogeneous Linear Agents
In this paper, we propose a multiplex proportional-integral approach, for
solving consensus problems in networks of heterogeneous nodes dynamics affected
by constant disturbances. The proportional and integral actions are deployed on
two different layers across the network, each with its own topology. Sufficient
conditions for convergence are derived that depend upon the structure of the
network, the parameters characterizing the control layers and the node
dynamics. The effectiveness of the theoretical results is illustrated using a
power network model as a representative example.Comment: 13 pages, 6 Figures, Preprint submitted to Automatic
An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination
This article reviews some main results and progress in distributed
multi-agent coordination, focusing on papers published in major control systems
and robotics journals since 2006. Distributed coordination of multiple
vehicles, including unmanned aerial vehicles, unmanned ground vehicles and
unmanned underwater vehicles, has been a very active research subject studied
extensively by the systems and control community. The recent results in this
area are categorized into several directions, such as consensus, formation
control, optimization, task assignment, and estimation. After the review, a
short discussion section is included to summarize the existing research and to
propose several promising research directions along with some open problems
that are deemed important for further investigations
Fast Consensus Tracking of Multiagent Systems with Diverse Communication Delays and Input Delays
The consensus tracking problem for discrete-time multiagent systems with input and communication delays is studied. A sufficient condition is obtained over a directed graph based on the frequency-domain analysis. Furthermore, a fast decentralized consensus tracking conditions based on
increment PID algorithm are discussed for improving convergence speed of the multiagent systems. Based on this result, genetic algorithm is introduced to construct increment PID based on genetic algorithm for obtaining optimization consensus tracking performance. Finally, a numerable example is given to compare convergence speed of three tracking algorithms in the same condition. Simulation results show the effectiveness of the proposed algorithm
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