Nonlinear model structure identification using genetic programming (original) (raw)

Gray, G.J., Murray-Smith, D.J., Li, Y. ORCID: https://orcid.org/0000-0002-6575-1839, 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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Abstract

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.

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Funder and Project Information

1

Evolutionary programming for nonlinear control

Yun Li

GR/K24987

Systems Power and Energy

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