7 research outputs found
Robust Consensus Tracking of Heterogeneous Multi-Agent Systems under Switching Topologies
In this paper, we consider a robust consensus tracking problem of
heterogeneous multi-agent systems with time-varying interconnection topologies.
Based on common Lyapunov function and internal model techniques, both state and
output feedback control laws are derived to solve this problem. The proposed
design is robust by admitting some parameter uncertainties in the multi-agent
system.Comment: 11 pages, 4 figures, accepte
On Distributed Internal Model Principle for Output Regulation over Time-Varying Networks of Linear Heterogeneous Agents
We study a multi-agent output regulation problem, where not all agents have
access to the exosystem's dynamics. We propose a distributed controller that
solves the problem for linear, heterogeneous, and uncertain agent dynamics as
well as time-varying directed networks. The distributed controller consists of
two parts: (1) an exosystem generator that creates a local copy of the
exosystem dynamics by using consensus protocols, and (2) a dynamic compensator
that uses (again) consensus to approach the internal model of the exosystem and
thereby achieves perfect output regulation. Our approach leverages methods from
internal model based controller synthesis, multi-agent consensus over directed
networks, and stability of time-varying linear systems; the derived result is
an adaptation of the (centralized) internal model principle to the distributed,
networked setting
Cooperative Robust Output Regulation Problem for Discrete-Time Linear Time-Delay Multi-Agent Systems
In this paper, we study the cooperative robust output regulation problem for
discrete-time linear multi-agent systems with both communication and input
delays by distributed internal model approach. We first introduce the
distributed internal model for discrete-time multi-agent systems with both
communication and input delays. Then, we define so-called auxiliary system and
auxiliary augmented system. Finally, we solve our problem by showing, under
some standard assumptions, that if a distributed state feedback control or a
distributed output feedback control solves the robust output regulation problem
of the auxiliary system, then the same control law solves the cooperative
robust output regulation problem of the original multi-agent systems.Comment: arXiv admin note: text overlap with arXiv:1508.0420
Internal Model Approach to Cooperative Robust Output Regulation for Linear Uncertain Time-Delay Multi-Agent Systems
In this paper, we study the cooperative robust output regulation problem for
linear uncertain multi-agent systems with both communication delay and input
delay by the distributed internal model approach. The problem includes the
leader-following consensus problem of linear multi-agent systems with
time-delay as a special case. We first generalize the internal model design
method to systems with both communication delay and input delay. Then, under a
set of standard assumptions, we have obtained the solution of the problem via
both the state feedback control and the output feedback control. In contrast
with the existing results, our results apply to general uncertain linear
multi-agent systems, accommodate a large class of leader signals, and achieve
the asymptotic tracking and disturbance rejection at the same time.Comment: 15 pages, 3 figure
A hybrid approach for cooperative output regulation with sampled compensator
This work investigates the cooperative output regulation problem of linear
multi-agent systems with hybrid sampled data control. Due to the limited data
sensing and communication, in many practical situations, only sampled data are
available for the cooperation of multi-agent systems. To overcome this problem,
a distributed hybrid controller is presented for the cooperative output
regulation, and cooperative output regulation is achieved by well designed
state feedback law. Then it proposed a method for the designing of sampled data
controller to solve the cooperative output regulation problem with continuous
linear systems and discrete-time communication data. Finally, numerical
simulation example for cooperative tracking and a simulation example for
optimal control of micro-grids are proposed to illustrate the result of the
sampled data control law
Cooperative Global Robust Output Regulation for a Class of Nonlinear Multi-Agent Systems by Distributed Event-Triggered Control
This paper studies the event-triggered cooperative global robust output
regulation problem for a class of nonlinear multi-agent systems via a
distributed internal model design. We show that our problem can be solved
practically in the sense that the ultimate bound of the tracking error can be
made arbitrarily small by adjusting a design parameter in the proposed
event-triggered mechanism. Our result offers a few new features. First, our
control law is robust against both external disturbances and parameter
uncertainties, which are allowed to belong to some arbitrarily large prescribed
compact sets. Second, the nonlinear functions in our system do not need to
satisfy the global Lipchitz condition. Thus our systems are general enough to
include some benchmark nonlinear systems that cannot be handled by existing
approaches. Finally, our control law is a specific distributed output-based
event-triggered control law, which lends itself to a direct digital
implementation.Comment: This paper has been submitted to a journal on July 17, 201
Time-Varying Formation Control of a Collaborative Multi-Agent System Using Negative-Imaginary Systems Theory
The movement of cooperative robots in a densely cluttered environment may not
be possible if the formation type is invariant. Hence, we investigate a new
method for time-varying formation control for a group of heterogeneous
autonomous vehicles, which may include Unmanned Ground Vehicles (UGV) and
Unmanned Aerial Vehicles (UAV). We have extended a Negative-Imaginary (NI)
consensus control approach to switch the formation shape of the robots whilst
only using the relative distance between agents and between agents and
obstacles. All agents can automatically create a new safe formation to overcome
obstacles based on a novel geometric method, then restore the prototype
formation once the obstacles are cleared. Furthermore, we improve the position
consensus at sharp corners by achieving yaw consensus between robots.
Simulation and experimental results are then analyzed to validate the
feasibility of our proposed approach