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Adaptive Hierarchical Multiple Models to Control Dynamic Systems

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-08-C-0023
Agency Tracking Number: F074-012-0320
Amount: $100,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF07-T012
Solicitation Number: N/A
Solicitation Year: 2007
Award Year: 2008
Award Start Date (Proposal Award Date): 2007-10-31
Award End Date (Contract End Date): 2008-07-31
Small Business Information
500 West Cummings Park - Ste 3000
Woburn, MA 01801
United States
DUNS: 859244204
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Ssu-Hsin Yu
 Manager of Research & Development
 (781) 933-5355
Business Contact
 Jay Miselis
Title: Corporate Controller
Phone: (781) 933-5355
Research Institution
 Robert Jacobs
Dept of Brain and Cognitive Sc
Rochester, NY 14627
United States

 (585) 275-0753
 Nonprofit college or university

Modern control theory offers mathematically rigorous and powerful solutions to many dynamic systems. Its limitations are that the classes of dynamic systems covered by the theory are limited to linear systems or certain well-structured nonlinear systems, and the adaptation of the controllers are often slow if the controller parameters are far away from their desired values. On the other hand, the ability of humans to learn to control complex dynamic systems while adapting to changing environments and objectives arises from many mental strategies we employ. Among them are dividing a complex task into smaller manageable subtasks, making use of ``experience with analogous tasks'', and adapting and combining solutions from similar tasks instead of starting from scratch. Motivated by the above observations, we propose a hierarchical multiple models approach to bridge the gap between humans' superior ability to conduct high-level planning and quick adaptation based on prior experience, and the advances of modern control theory in performing low-level control actions for well-structured systems very effectively. Our team consists of Scientific Systems Company, Inc. (SSCI) as the prime contractor, and Professor Robert Jacobs of University of Rochester as a subcontractor for this project.

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

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