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Stable High Bandwidth AO Control with physical DM constraints

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9451-20-C-0529
Agency Tracking Number: F18A-008-0178
Amount: $749,979.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: AF18A-T008
Solicitation Number: 18.A
Timeline
Solicitation Year: 2018
Award Year: 2020
Award Start Date (Proposal Award Date): 2019-10-07
Award End Date (Contract End Date): 2021-10-07
Small Business Information
1501 S. Sunset St. Suite C
Longmont, CO 80501
United States
DUNS: 079204036
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Troy Rhoadarmer
 President
 (720) 684-8069
 troy.rhoadarmer@guidestaroptical.com
Business Contact
 Aaron Buckner
Phone: (310) 435-5492
Email: aaron.buckner@guidestaroptical.com
Research Institution
 University of California Los Angeles
 Elaine Tom Elaine Tom
 
UCLA Mechanical and Aerospace Engineering Department BOX 951597, 48-121 E4
Los Angeles, CA 90095
United States

 (310) 794-6225
 Nonprofit college or university
Abstract

Adaptive optics (AO) can compensate for the aberrating effects of atmospheric turbulence which degrade the performance of high energy laser (HEL) weapon systems and, as such, is an enabling technology for effective deployment of HEL weapon systems. A key component in an HEL AO system is the deformable mirror (DM). However, mechanical constraints in currently available DMs limits AO system performance in stressing engagements. Guidestar teamed with UCLA to develop methods that can provide AO performance with a constrained DM that is comparable to performance with an ideal DM that does not have these physical constraints. Guidestar developed a conjugate gradient method that determined an optimal DM command without violating hardware limitations in a woofer-tweeter control architecture. This method tied together within an adaptive Model Predictive Control (MPC) framework developed by UCLA. In this proposed Phase II program, Guidestar and UCLA will advance the development of these approaches, creating a complete control architecture to provide optimal AO correction using a DM that is constrained by total stroke saturation and inter-actuator stroke limits. Our approach will be validated through modeling and simulation, as well as scaled laboratory testing of the DM control methods.

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

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