NEURAL NETWORKS, YOULA PARAMETERIZATION AND RECONFIGURABLE CONTROL SYSTEM

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: N/A
Agency Tracking Number: 21688
Amount: $300,000.00
Phase: Phase II
Program: SBIR
Awards Year: 1995
Solitcitation Year: N/A
Solitcitation Topic Code: N/A
Solitcitation Number: N/A
Small Business Information
Accurte Automation Corp.
7001 Shallowford Rd, Chattanooga, TN, 37421
Duns: N/A
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Richard E Saeks
 (615) 894-4646
Business Contact
Phone: () -
Research Institution
N/A
Abstract
RESEARCHERS ARE INVESTIGATING A NEW CONTROL ARCHITECTURE IN WHICH A NEURAL NETWORK IS USED TO SET THE COEFFICIENTS OF THE YOULA PARAMETER FOR THE CONTROLLER. THE "DESIGN BY LEARNING" BENEFITS ASSOCIATED WITH NEURAL CONTROL ARE REALIZED BY THE APPROACH WHILE SIMULTANEOUSLY GUARANTEEING THAT THE RESULTANT SYSTEM IS STABLE. THE ARCHITECTURE YIELDS A RECONFIGURABLE SYSTEM IN WHICH THE NEURAL NETWORK AUTOMATICALLY UPDATES THE YOULA PARAMETER WHENEVER A NEW REFERENCE INPUT OR PERFORMANCE CRITERIA IS SPECIFIED. SPECIFIC RESEARCH OBJECTIVES INCLUDE THE DEVELOPMENT OF NEURAL NETWORK ARCHITECTUERS AND TRAINING METHODS APPLICABLE TO THE SYSTEM; FORMULATION OF METHODS FOR UPDATING THE NETWORK TRAINING EACH TIME THE SYSTEM IS OPERATED; IMPLEMENTATION OF THE CONTROLLER AS AN AUTO-RECONFIGURABLE SYSTEM; AND APPLICATION OF THE NEURAL CONTROLLER TO FLIGHT CONTROL SYSTEMS AND ROBOTICS.

* information listed above is at the time of submission.

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