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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 IASTED CONTROL AND APPLICATIONS

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Coordination of Multi-Agent Systems

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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


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

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  • 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

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More Examples from Nature

A Swarm of Locusts

Synchronously Flashing Fireflies

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Examples from Engineering

Autonomous Formation Flying and UAV Networks

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Examples from Social Dynamics and Engineering Systems

Mobile Robot Networks

Crowd Dynamics and Building Egress

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Example from Bilateral Teleoperation

Multi-Robot Remote Manipulation

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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

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Synchronization of Metronomes


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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?

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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.

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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

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Definition of A Passive System

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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


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Passivity of Lagrangian Systems

More generally, an N-DOF Lagrangian system


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

from input to output

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Graph Theory

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Examples of Communication Graphs


All-to-All Coupling

(Balanced -Undirected)

Directed – Not Balanced

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Synchronization of Multi-Agents

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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.

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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.

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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.

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Further Extensions

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

where is a (passive) nonlinearity of the form

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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.

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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

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Nonlinear Positive-Real Lemma

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

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Barbalat’s Lemma can be used to show that

and, therefore,

Connectivity of the graph interconnection then implies output synchronization.

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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

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The closed loop system is therefore

and the outputs (states) synchronize as shown

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Second-Order Example

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

connected in a ring topology

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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


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coupling the passive outputs leads to

and the agents synchronize as shown below

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Simulation Results

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Example: Coupled Pendula

Consider two coupled pendula with dynamics

and suppose

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is the phase of the i-th oscillator,


Kuramoto Oscillators

Kuramoto Oscillators are systems of the form

is the natural frequency and is the coupling strength.

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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

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Multi-Robot Coordination With Delay

Consider a network of N Lagrangian systems

As before, define the input torque as

which yields


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Coupling the passive outputs yields

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.

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  • 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.

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