Online modelling based on Genetic Programming. (20th February 2007)

• Record Type: Journal Article
• Authors: Winkler, Stephan; Efendic, Hajrudin; Del Re, Luigi; Affenzeller, Michael; , Stefan Wagner
• Is Part Of: International journal of intelligent systems technologies and applications. Volume 2:Number 2/3(2007)
• Page Start: 255
• Page End: 270
• Publication Date: 2007-02-20
• Subjects: genetic programming -- GP -- data driven model identification -- self-adaption -- machine learning -- online modelling -- fault diagnosis -- automatic learning -- real time; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 006.3
• Languages: English
• ISSNs: 1740-8865

Abstract

Genetic Programming (GP), a heuristic optimisation technique based on the theory of Genetic Algorithms (GAs), is a method successfully used to identify non-linear model structures by analysing a system's measured signals. Mostly, it is used as an offline tool that means that structural analysis is done after collecting all available identification data. In this paper, we propose an enhanced on-line GP approach that is able to adapt its behaviour to new observations while the GP process is executed. Furthermore, an approach using GP for online Fault Diagnosis (FD) is described, and finally test results using measurement data of NOx emissions of a BMW diesel engine are discussed.