6,100 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
Distributed Robust Consensus Control of Multi-agent Systems with Heterogeneous Matching Uncertainties
This paper considers the distributed consensus problem of linear multi-agent
systems subject to different matching uncertainties for both the cases without
and with a leader of bounded unknown control input. Due to the existence of
nonidentical uncertainties, the multi-agent systems discussed in this paper are
essentially heterogeneous. For the case where the communication graph is
undirected and connected, a distributed continuous static consensus protocol
based on the relative state information is first designed, under which the
consensus error is uniformly ultimately bounded and exponentially converges to
a small adjustable residual set. A fully distributed adaptive consensus
protocol is then designed, which, contrary to the static protocol, relies on
neither the eigenvalues of the Laplacian matrix nor the upper bounds of the
uncertainties. For the case where there exists a leader whose control input is
unknown and bounded, distributed static and adaptive consensus protocols are
proposed to ensure the boundedness of the consensus error. It is also shown
that the proposed protocols can be redesigned so as to ensure the boundedness
of the consensus error in the presence of bounded external disturbances which
do not satisfy the matching condition. A sufficient condition for the existence
of the proposed protocols is that each agent is stabilizable.Comment: 16 page, 10 figures. This manuscript is an extended version of our
paper accepted for publication by Automatic
Robust Cooperative Manipulation without Force/Torque Measurements: Control Design and Experiments
This paper presents two novel control methodologies for the cooperative
manipulation of an object by N robotic agents. Firstly, we design an adaptive
control protocol which employs quaternion feedback for the object orientation
to avoid potential representation singularities. Secondly, we propose a control
protocol that guarantees predefined transient and steady-state performance for
the object trajectory. Both methodologies are decentralized, since the agents
calculate their own signals without communicating with each other, as well as
robust to external disturbances and model uncertainties. Moreover, we consider
that the grasping points are rigid, and avoid the need for force/torque
measurements. Load distribution is also included via a grasp matrix
pseudo-inverse to account for potential differences in the agents' power
capabilities. Finally, simulation and experimental results with two robotic
arms verify the theoretical findings
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