Nonlinear model structure identification using genetic programming

Gray, G.J., Murray-Smith, D.J., Li, Y. and Sharman, K.C. (1996) Nonlinear model structure identification using genetic programming. In: Genetic Programming '96 Conference (GP '96), Stanford, CA, 28-31 Jul 1996, pp. 32-37.

Abstract

Genetic programming can be used to eveolve an algebraic expression as part of an equation representing measured input-output response data. Parts of the nonlinear differential equations describing a dynamic system are identified along with their numerical parameters using genetic programming. The results of several such optimisations are analysed to produce a nonlinear physical representation of the dynamic system. This method is applied to the identification of fluid flow through pipes in a coupled water tank system. A representative nonlinear model is identified.

• Item Type: Conference Proceedings
• Additional Information: Published in: Koza, J.R. (ed.) <i>Late Breaking Papers at the Genetic Programming 1996 Conference</i>. Stanford: Stanford University Press, 1996. ISBN: 9780182010318.
• Keywords: Genetic programming, dynamic model, nonlinear, optimisation, system identification, fluid flow.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Murray-Smith, Professor David and Li, Professor Yun
• Authors: Gray, G.J., Murray-Smith, D.J., Li, Y., and Sharman, K.C.
• Subjects: Q Science > QA Mathematics > QA76 Computer software; T Technology > TJ Mechanical engineering and machinery; T Technology > TK Electrical engineering. Electronics Nuclear engineering
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy