GENETIC ADAPTIVE FAILURE ESTIMATION
In this paper, the authors present a genetic algorithm based method that can perform online adaptive failure estimate for a nonlinear automated highway system (AHS). After describing how to construct a genetic adaptive parameter estimator, the authors illustrate the operation and performance of the estimator be using it to track certain parameters for a vehicle in an AHS setting.
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Supplemental Notes:
- Publication Date: 1997 Published By: American Automatic Control Council, Evanston IL
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Corporate Authors:
University of California, Berkeley
Department of Mechanical Engineering
Berkeley, CA United States 94720-1740University of California, Berkeley
California PATH Program, Institute of Transportation Studies
Richmond Field Station, 1357 South 46th Street
Richmond, CA United States 94804-4648Ohio State University, Columbus
Department of Electrical Engineering
Columbus, OH United States 43210University of California, Berkeley
Department of Electrical Engineering and Computer Sciences
Berkeley, CA United States 94720New Jersey Institute of Technology, Newark
Department of Electrical and Computer Engineering
Newark, NJ United States 07102University of California, Berkeley
Intelligent Machinges and Robotics Laboratory
Berlkeley, CA United StatesUniversity of Southern California, Los Angeles
Department of Industrial and Systems Engineering, 3715 McClintock Avenue
Los Angeles, CA United States 90089-0193Ford Motor Company
Scientific and Research Laboratory
Dearborn, MI United States 48124 -
Authors:
- Gremling, J R
- Passino, K M
- Conference:
- Publication Date: 1997
Language
- English
Media Info
- Pagination: p. 908-912
Subject/Index Terms
- TRT Terms: Automated highways; Computer algorithms; Fault monitoring
- Subject Areas: Highways;
Filing Info
- Accession Number: 00776716
- Record Type: Publication
- Source Agency: UC Berkeley Transportation Library
- Files: PATH
- Created Date: Nov 17 1999 12:00AM