Coordination of multi agent systems
Download
1 / 40

Coordination of Multi-Agent Systems - PowerPoint PPT Presentation


  • 396 Views
  • Updated On :

Coordination of Multi-Agent Systems. Mark W. Spong Donald Biggar Willett Professor Department of Electrical and Computer Engineering and The Coordinated Science Laboratory University of Illinois at Urbana-Champaign, USA [email protected] IASTED CONTROL AND APPLICATIONS

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Coordination of Multi-Agent Systems' - erika


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Coordination of multi agent systems l.jpg

Coordination of Multi-Agent Systems

Mark W. Spong

Donald Biggar Willett Professor

Department of Electrical and Computer Engineering

and The Coordinated Science Laboratory

University of Illinois at Urbana-Champaign, USA

[email protected]

IASTED CONTROL AND APPLICATIONS

May 24-26, 2006, Montreal, Quebec, Canada


Introduction l.jpg
Introduction

  • The problem of coordination of multiple agents arises in numerous applications, both in natural and in man-made systems.

  • Examples from nature include:

Flocking of Birds

Schooling of Fish


Slide3 l.jpg

More Examples from Nature

A Swarm of Locusts

Synchronously Flashing Fireflies


Examples from engineering l.jpg
Examples from Engineering

Autonomous Formation Flying and UAV Networks


Examples from social dynamics and engineering systems l.jpg
Examples from Social Dynamics and Engineering Systems

Mobile Robot Networks

Crowd Dynamics and Building Egress


Example from bilateral teleoperation l.jpg
Example from Bilateral Teleoperation

Multi-Robot Remote Manipulation


Other examples l.jpg
Other Examples

  • Other Examples:

    • circadian rhythm

    • contraction of coronary pacemaker cells

    • firing of memory neurons in the brain

    • Superconducting Josephson junction arrays

    • Design of oscillator circuits

    • Sensor networks



Fundamental questions l.jpg
Fundamental Questions

In order to analyze such systems and design coordination strategies, several questions must be addressed:

  • What are the dynamics of the individual agents?

  • How do the agents exchange information?

  • How do we couple the available outputs to achieve synchronization?


Fundamental assumptions l.jpg
Fundamental Assumptions

In this talk we assume:

  • that the agents are governed by passive dynamics.

  • that the information exchange among agents is described by a balanced graph, possibly with switching topology and time delays in communication.


Outline of results l.jpg
Outline of Results

We present a unifying approach to:

  • Output Synchronization of Passive Systems

  • Coordination of Multiple Lagrangian Systems

  • Bilateral Teleoperation with Time Delay

  • Synchronization of Kuramoto Oscillators



Examples of passive systems l.jpg
Examples of Passive Systems

In much of the literature on multi-agent systems, the agents are modeled as first-order integrators

This is a passive system with storage function

since


Passivity of lagrangian systems l.jpg
Passivity of Lagrangian Systems

More generally, an N-DOF Lagrangian system

satisfies

where H is the total energy. Therefore, the system is passive

from input to output


Graph theory l.jpg

3

2

1

4

Graph Theory


Examples of communication graphs l.jpg

3

2

3

2

4

1

5

1

4

3

2

1

4

Examples of Communication Graphs

Balanced-Directed

All-to-All Coupling

(Balanced -Undirected)

Directed – Not Balanced



First results l.jpg
First Results

Suppose the systems are coupled by the control law

where K is a positive gain and is the set of agents communicating with agent i.

Theorem: If the communication graph is weakly connected and balanced, then the system is globally stable and the agents output synchronize.


Some corollaries l.jpg
Some Corollaries

1) If the agents are governed by identical linear dynamics

then, if (C,A) is observable, output synchronization implies state synchronization

2) In nonlinear systems without drift, the outputs converge to a common constant value.


Some extensions l.jpg
Some Extensions

We can also prove output synchronization for systems with delay and dynamically changing graph topologies, i.e.

provide the graph is weakly connected pointwise in time and there is a unique path between nodes i and j.


Further extensions l.jpg
Further Extensions

We can also prove output synchronization when the coupling between agents is nonlinear,

where is a (passive) nonlinearity of the form


Technical details l.jpg
Technical Details

  • The proofs of these results rely on methods from Lyapunov stability theory, Lyapunov-Krasovski theory and passivity-based control together with graph theoretic properties of the communication topology.

  • References:

    [1] Nikhil Chopra and Mark W. Spong, “Output Synchronization of Networked Passive Systems,” IEEE Transactions on Automatic Control, submitted, December, 2005

    [2] Nikhil Chopra and Mark W. Spong, “Passivity-Based Control of Multi-Agent Systems,” in Advances in Robot Control: From Everyday Physics to Human-Like Movement, Springer-Verlag, to appear in 2006.


Technical details23 l.jpg
Technical Details

Since each agent is assumed to be passive, let

,…,

be the storage functions for the N agents

and define the Lyapunov-Kraskovski functional



Slide25 l.jpg

Now, after some lengthy calculations, using Moylan’s theorem and assuming that the interconnection graph is balanced, one can show that


Slide26 l.jpg

Barbalat’s Lemma can be used to show that theorem and assuming that the interconnection graph is balanced, one can show that

and, therefore,

Connectivity of the graph interconnection then implies output synchronization.


Some examples l.jpg

3 theorem and assuming that the interconnection graph is balanced, one can show that

2

1

4

Some Examples

Consider four agents coupled in a ring topology with dynamics

Suppose there is a constant delay T in communication and let the control input be


Slide28 l.jpg

The closed loop system is therefore theorem and assuming that the interconnection graph is balanced, one can show that

and the outputs (states) synchronize as shown


Second order example l.jpg

3 theorem and assuming that the interconnection graph is balanced, one can show that

2

1

4

Second-Order Example

Consider a system of four point masses with second-order dynamics

connected in a ring topology


Slide30 l.jpg

The key here is to define ``the right’’ passive output. Define a preliminary feedback

so that the dynamic equations become

where which is passive from

to


Slide31 l.jpg

coupling the passive outputs leads to Define a preliminary feedback

and the agents synchronize as shown below


Slide32 l.jpg

Simulation Results Define a preliminary feedback


Example coupled pendula l.jpg
Example: Coupled Pendula Define a preliminary feedback

Consider two coupled pendula with dynamics

and suppose


Kuramoto oscillators l.jpg

is the phase of the i-th oscillator, Define a preliminary feedback

where

Kuramoto Oscillators

Kuramoto Oscillators are systems of the form

is the natural frequency and is the coupling strength.


Slide36 l.jpg

Suppose that the oscillators all have the same natural frequency and define

Then we can write the system as

and our results immediately imply synchronization


Multi robot coordination with delay l.jpg
Multi-Robot Coordination With Delay frequency and define

Consider a network of N Lagrangian systems

As before, define the input torque as

which yields

where


Slide38 l.jpg

Coupling the passive outputs yields frequency and define

and one can show asymptotic state synchronization. This gives new results in bilateral teleoperation without the need for scattering or wave variables, as well as new results on multi-robot coordination.


Conclusions l.jpg
Conclusions frequency and define

  • The concept of Passivity allows a number of results from the literature on multi-agent coordination, flocking, consensus, bilateral teleoperation, and Kuramoto oscillators to be treated in a unified fashion.


Thank you l.jpg
THANK YOU! frequency and define

QUESTIONS?


ad