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Sufficient Statistics for System of Systems Control (S4C)

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-16-C-7604
Agency Tracking Number: B15C-002-0072
Amount: $100,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: MDA15-T002
Solicitation Number: 2016.0
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-04-25
Award End Date (Contract End Date): 2016-11-24
Small Business Information
15400 Calhoun Drive
Rockville, MD 20855
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Devendra Tolani
 (301) 294-4630
Business Contact
 Mark James
Phone: (301) 294-5221
Research Institution
 Stanford University
 Prof. Sanjay Lall
3160 Porter Drive, Suite 100
Palo Alto, CA 94304
United States

 (650) 723-1343
 Nonprofit College or University

There is an urgent need to develop and demonstrate innovative control, design and analysis techniques to characterize the stability and performance of a system of systems (SoS) as a function of sub-system dynamics, network structure and control/decision processes. This is particularly true in the missile defense scenario, which involves a coordinated defense against threats. However, there is no existing theory that can guarantee stability and performance of such networked control systems. To address this need, Intelligent Automation, Inc. and Stanford University, propose to develop a control theoretic framework for analysis and design of system of interacting control systems. This framework leverages on our teams prior work on developing sufficient statistics for optimal control of multi-agent systems. These statistics were developed for certain problems of linear systems and extended to particular classes of nonlinear systems as well. In this effort, we will further generalize the results to more general classes of systems and extend them to complex nonlinear and Multi-Input Multi-Output systems. We will study the computational aspects and trade-offs between performance and approximate solutions. This effort will lay the foundation for systematic control, design and analysis of complex real-world SoS with nonlinearity, uncertainties and communication delays. Approved for Public Release 16-MDA-8620 (1 April 16)

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

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