Adaptive Hierarchical Multiple Models to Control Dynamic Systems

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$100,000.00
Award Year:
2008
Program:
STTR
Phase:
Phase I
Contract:
FA9550-08-C-0023
Award Id:
85090
Agency Tracking Number:
F074-012-0320
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
859244204
Principal Investigator:
Ssu-HsinYu
Manager of Research & Development
(781) 933-5355
syu@ssci.com
Business Contact:
JayMiselis
Corporate Controller
(781) 933-5355
jmiselis@ssci.com
Research Institute:
UNIV. OF ROCHESTER
Robert Jacobs
Dept of Brain and Cognitive Sc
Rochester, NY, 14627
(585) 275-0753
Nonprofit college or university
Abstract
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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