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Integrating Prognostics in Automated Contingency Management Strategies for Advanced Aircraft Controls

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX09CB61C
Agency Tracking Number: 070012
Amount: $599,895.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2009
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
200 Canal View Blvd, Suite 300
Rochester, NY 14623
United States
DUNS: 073955507
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Gregory Kacprzynski
 Principal Investigator
 () -
 Greg.Kacprzynski@impact-tek.com
Business Contact
 Carol Marquardt
Title: Business Official
Phone: (585) 627-1923
Research Institution
 Georgia Tech Research Coroporation
 
505 Tenth Street, NW
Atlanta, GA 30318 5775
United States

 (404) 894-6929
 Domestic Nonprofit Research Organization
Abstract

Automated Contingency Management (ACM) is an emerging and game-changing area of engineering and scientific research that integrates prognostics and health management concept and intelligent control. As leaders in this field, Impact Technologies and Georgia Institute of Technology, propose to build off a strong foundation of ACM research performed with NASA and DARPA in the past few years to both mature the applicability of ACM technology for real aerospace components and push the envelop on the capability and breadth of the technology itself. A prognostics-enhanced, three-tiered ACM architecture for critical aerospace systems has been conceptualized and demonstrated in Phase I. The proposed Phase II effort is focusing on utilizing prognostics at the higher levels of the control hierarchy and is introducing novel concepts to address the fault-tolerant control design at the middle level from the areas of model predictive control, system dynamic inversion, intelligent search techniques, and optimization / system identification algorithms for mission adaptation at the high level. Game theoretic notions are exploited to distribute optimally the available control authority between the components. An electromechanical flight actuator and a UAV platform will be utilized as testbeds for performance evaluation. Significant benefits are anticipated to NASA, DoD, and industry.

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

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