Title :
Genetic adaptive failure estimation [automated highway system]
Author :
Gremling, James R. ; Passino, Kevin M.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
We develop a genetic algorithm (GA) based method that can perform online adaptive failure estimation for a nonlinear automated highway system (AHS). First, we show how to construct a genetic adaptive parameter estimator where a GA evolves the best set of parameter estimates for a known model structure in real time. Next, we illustrate the operation and performance of the genetic adaptive parameter estimator by using it to track certain parameters for an automobile in an AHS application
Keywords :
adaptive estimation; automated highways; fault diagnosis; genetic algorithms; nonlinear systems; parameter estimation; AHS; automobile; genetic adaptive failure estimation; nonlinear automated highway system; Automated highways; Automobiles; Biological cells; Equations; Genetic algorithms; Genetic engineering; Genetic mutations; Parameter estimation; Road vehicles; State estimation;
Conference_Titel :
American Control Conference, 1997. Proceedings of the 1997
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-3832-4
DOI :
10.1109/ACC.1997.609658
