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Control of Cooperative Engagements with Robust and Distributed Optimization (Concerto(TM))

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-06-C-0119
Agency Tracking Number: F054-011-0084
Amount: $749,717.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: AF05-T011
Solicitation Number: N/A
Timeline
Solicitation Year: 2005
Award Year: 2006
Award Start Date (Proposal Award Date): 2006-09-25
Award End Date (Contract End Date): 2008-09-25
Small Business Information
Suite A 75 Aero Camino
Goleta, CA 93117
United States
DUNS: 054672662
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Gaemus Collins
 Analyst
 (805) 968-6787
 gcollins@toyon.com
Business Contact
 Marcella Lindbery
Title: Director of Finance and C
Phone: (805) 968-6787
Email: mlindbery@toyon.com
Research Institution
 UNIV. OF CALIFORNIA, SANTA BARBARA
 Nancy R Lewis
 
Office of Research 3227 Cheadle Hall, UCSB
Santa Barbara, CA 93106
United States

 (805) 893-4034
 Nonprofit College or University
Abstract

Toyon Research Corporation and the University of California at Santa Barbara (UCSB) propose to develop decision and control algorithms for cooperative agents operating under an intermittent asynchronous communication network. Agents will be expected to perform a variety of cooperative missions such as persistent intelligence, surveillance, and reconnaissance (ISR), target search, acquisition, and tracking, area denial, and battle damage assessment under dynamically-varying bandwidth limitations, intermittent communications, and limited information. The key feature of the proposed cooperative control system is the use of an estimator-based distributed control (EBDC) architecture, allowing each UAV to internally model and anticipate the actions of the others UAVs. Under this EBDC architecture, the control system can gracefully scale from essentially centralized control (complete and perfect inter-vehicle communication) to completely distributed control (no inter-vehicle communication). The estimator-based distributed architecture models a centralized design by forcing each individual agent in the system to compute future control actions for all agents, as a function of the agents' positions and the global information state (GIS). The quality and amount of communication between agents determines the accuracy of each agent's GIS estimate. Each agent's GIS estimate, in turn, determines the accuracy of each agent's control estimates for the other agents. In this way, the EBDC algorithms transition from an essentially centralized solution to a completely decentralized solution based on the communication rate and information available to each agent within the cooperative network. The performance of the system will be guaranteed to degrade gracefully with the level of information available to each agent, because the EBDC algorithms optimize the control actions based on the existing information instead of attempting to optimize the communication network to allow better throughput. In the Phase II effort, Toyon and UCSB will enhance and refine the EBDC algorithms developed under Phase I. Implementation of these algorithms will continue in both MATLAB and Toyon's higher-fidelity SLAMEM(TM) simulation tool. We will test and demonstrate their effectiveness in cooperative search and tracking scenarios under varying levels of information throughput. Bandwidth limitations, time delays with uncertain intervals, and network topology limitations will be incorporated into the simulation. The extent of reliable communications required to ensure robust cooperative control will be evaluated.

* Information listed above is at the time of submission. *

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