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January 28, 2013

Mtg: Cooperative Multiagent Control: Stability vs. Optimality

by @ 12:50 pm. Filed under ALL, Communications, Electronics Design, Engineering Mgmt

THURSDAY February 21, 2013
SCV Control Systems Chapter
Speaker: Prof. Frank L. Lewis, Advanced Controls and Sensors Group, UT-Arlington
Time: 6:30 PM
Cost: none
Place: Intersil, 1001 Murphy Ranch Road, Milpitas
RSVP: from website

Distributed systems of agents linked by communication networks only have access to information from their neighboring agents, yet must achieve global agreement on team activities to be performed cooperatively.? Examples include networked manufacturing systems, wireless sensor networks, networked feedback control systems, and the internet.? Sociobiological groups such as flocks, swarms, and herds have built-in mechanisms for cooperative control wherein each individual is influenced only by its nearest neighbors, yet the group achieves consensus behaviors such as heading alignment, leader following, exploration of the environment, and evasion of predators.? It was shown by Charles Darwin that local interactions between population groups over long time scales lead to global results such as the evolution of species.
Natural decision systems incorporate notions of optimality, since the resources available to organisms and species are limited.? This talk investigates relations between the stability of cooperative control and optimality of cooperative control.
Stability:? A method is given for the design of cooperative feedbacks for the continuous-time multi-agent tracker problem (also called pinning control or leader-following) that guarantees stable synchronization on arbitrary graphs with spanning trees.? It is seen that this design is a locally optimal control with infinite gain margin.? In the case of the discrete-time cooperative tracker, local optimal design yields stability on graphs that satisfy an additional restriction based on the Mahler instability measure of the local agent dynamics.
Optimality:? Global optimal control of distributed systems is complicated by the fact that, for general LQR performance indices, the resulting optimal control is not distributed in form.? Therefore, it cannot be implemented on a prescribed communication graph topology.? A condition is given for the existence of any optimal controllers that be implemented in distributed fashion.? This condition shows that for the existence of global? optimal controllers of distributed form, the performance index weighting matrices must be selected to depend on the graph structure.

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