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Novel Algorithm/Hardware Partnerships for Real-Time Nonlinear Control

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-12-C-0035
Agency Tracking Number: F09B-T06-0234
Amount: $750,000.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: AF09-BT06
Solicitation Number: 2009.B
Timeline
Solicitation Year: 2009
Award Year: 2012
Award Start Date (Proposal Award Date): 2011-12-01
Award End Date (Contract End Date): N/A
Small Business Information
Suite 506 8939 South Sepulveda Blvd
Los Angeles, CA -
United States
DUNS: 036255409
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Yun Wang
 Vice President
 (310) 216-1677
 wang@tempest-tech.com
Business Contact
 Ben Fitzpatrick
Title: President
Phone: (310) 216-1677
Email: fitzpatrick@tempest-tech.com
Research Institution
 Wayne State University
 Donald J Wonsowicz
 
656 W. Kirby
Detroit, MI 48202-
United States

 (313) 577-6734
 Nonprofit College or University
Abstract

ABSTRACT: The real-time implementation of controls in nonlinear systems remains one of the great challenges in applying advanced control technology. Often, linearization around a set point is the only practical approach, and many controllers implemented in hardware systems are simple PID feedback mechanisms. To apply Pontryagin"s principle or Bellman"s equation using conventional hardware and algorithms for high dimensional nonlinear systems requires more computing power than is realistic. The success of linear control theory, especially certainty equivalence and LQG approaches, leads us to hope for additional gains from fully nonlinear controls. We propose an innovation in computational nonlinear control that offers ground breaking potential for real-time control applications, making fully nonlinear problems solvable with the computational efficiency of linear problems. Our Phase II effort will focus on a prototype hardware-software solution implementing max-plus arithmetic for efficient solution of nonlinear control and optimization problems. The success of our two-pronged Phase I effort in devising efficient algorithms based on max-plus structure and in studying and simulating reconfigurable computing hardware solutions for efficient max-plus implementation suggests significant potential for this approach. The result of Phase II work will be a prototype solution, including a software development kit and an optimization co-processor, for solving nonlinear optimization and control problems efficiently. BENEFIT: If the feasibility studies of Phase I can be extended to a functional prototype in Phase II, the result will revolutionize the field of control theory. The computational efficiency improvements we expect to see will permit fully nonlinear control techniques to be applied in crucial tracking and guidance systems and flight controls. Performance enhancements for unmanned systems will provide warfighters with greatly improved tools for surveillance and combat.

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

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