Performance analysis of distributed
control configurations in LQR multiagent system design
Ivana Tomić
Supervised by Professor George D. Halikias
City University London
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Motivation
Complex systems 
Cooperation required for
the coordinating behaviour
Centralized solutions
 Infeasible
 Impractical
Distributed control
 Local information exchange
 Neighbouring sets
Optimal!
Can we identify
optimal or nearoptimal schemes?
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Slide 2
Problem Definition
 Control of the multi-agent system
with limited information available
 Identical dynamically decoupled
agents
 Existing solution
 LQR-based design
 Size of a problem = max degree + 1
Guaranteed stabilizing controller, but there is
performance loss.
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Slide 3
Proposed Solution
Sufficient and necessary conditions have been derived for
optimality and near-optimality of a specific distributed
configurations.
1
2
1
2
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4
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Complete Graph vs.
Single Link Cut
Configurations
For single link cut configurations optimality always holds
if the initial vector lies is a certain subspace of state-space
which is identified.
Results are verified on a formation of experimental UAVs
described by 6-DOF dynamics.
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Slide 4
Simulation Results
Distributed control of linear and nonlinear UAV multi-agent system
Integral control of linear and nonlinear UAV multi-agent system
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Conclusion and future work
 Project Outcomes:
 Algorithm for finding near-optimal distributed configurations.
 Extension to distributed control with integral action.
 Can be successfully applied to high-order dynamical systems.
 Future Work:
 Generalize proofs for an arbitrary network.
 H∞ control of distributed configurations.
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Slide 6