Nonlinear model structure identification using genetic programming

Gray, G.J., Murray-Smith, D.J., Li, Y., Sharman, K.C., and Weinbrenner, T. (1998) Nonlinear model structure identification using genetic programming. Control Engineering Practice, 6(11), pp. 1341-1352. (doi:10.1016/S0967-0661(98)00087-2 )

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Genetic Programming is an optimisation procedure which may be applied to the identification of the nonlinear structure of a dynamic model from experimental data. In such applications, the model structure may be described either by differential equations or by a block diagram and the algorithm is configured to minimise the sum of the squares of the error between the recorded experimental response from the real system and the corresponding simulation model output. The technique has been applied successfully to the modelling of a laboratory scale process involving a coupled water tank system and to the identification of a helicopter rotor speed controller and engine from flight test data. The resulting models provide useful physical insight.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Gray, Dr Gary and Murray-Smith, Professor David and Li, Professor Yun
Authors: Gray, G.J., Murray-Smith, D.J., Li, Y., Sharman, K.C., and Weinbrenner, T.
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Research Group:Intelligent Systems
Journal Name:Control Engineering Practice
Publisher:Elsevier Science B.V.
Published Online:16 March 1999

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
101101Evolutionary programming for nonlinear controlYun LiScience & Engineering Research Council (SERC)GR/K24987Systems Power and Energy