Online modelling based on Genetic Programming

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 NO x emissions of a BMW diesel engine are discussed.

[1]  Zbigniew Michalewicz,et al.  Genetic algorithms + data structures = evolution programs (3rd ed.) , 1996 .

[2]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[3]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[4]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5]  Herbert A. Simon,et al.  Scientific discovery: compulalional explorations of the creative process , 1987 .

[6]  Michael Affenzeller,et al.  SASEGASA: A New Generic Parallel Evolutionary Algorithm for Achieving Highest Quality Results , 2004, J. Heuristics.

[7]  Stephan M. Winkler,et al.  NOx virtual sensor based on structure identification and global optimization , 2005 .

[8]  Herbert A. Simon,et al.  Scientific discovery , 1993, BMJ : British Medical Journal.

[9]  Huosheng Hu,et al.  Using Genetic Programming to Evolve Robot Behaviours , 2001 .

[10]  Riccardo Poli,et al.  Foundations of Genetic Programming , 1999, Springer Berlin Heidelberg.

[11]  A. Willsky,et al.  Analytical redundancy and the design of robust failure detection systems , 1984 .

[12]  Luigi del Re,et al.  Iterative Multi-Step Diagnosis Process for Engine Systems , 2005 .

[13]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[14]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[15]  Martin C. Martin,et al.  Genetic programming for real world robot vision , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  M. Affenzeller,et al.  Offspring Selection: A New Self-Adaptive Selection Scheme for Genetic Algorithms , 2005 .

[17]  David J. Murray-Smith,et al.  Nonlinear model structure identification using genetic programming , 1998 .

[18]  J.J. Gertler,et al.  Survey of model-based failure detection and isolation in complex plants , 1988, IEEE Control Systems Magazine.

[19]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[20]  Michael Affenzeller,et al.  HeuristicLab: A Generic and Extensible Optimization Environment , 2005 .

[21]  Stephan M. Winkler,et al.  New methods for the identification of nonlinear model structures based upon genetic programming techniques , 2005 .