Title :
Parametric modelling of a twin rotor system using genetic algorithms
Author :
Darus, I. Z Mat ; Aldebrez, F.M. ; Tokhi, M.O.
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, UK
Abstract :
System identification using parametric linear approaches for modelling a twin rotor multi-input multi-output system (TRMS) in hovering position is presented in this work. The utilisation of a genetic algorithm (GA) optimisation technique for dynamic modelling of a highly non-linear system is studied in comparison to the conventional recursive least squares (RLS) technique. The global search technique of GA is used to identify the parameters of the TRMS based on one-step-ahead prediction. A comparative assessment of the two models in characterising the system is carried out in the time and frequency domains. Experimental results indicate the advantages of GA over RLS in linear parametric modelling. The developed genetic-modelling approach will be used for control design and development in future work.
Keywords :
MIMO systems; aircraft control; genetic algorithms; helicopters; nonlinear systems; parameter estimation; rotors; genetic algorithms; global search technique; hovering position; linear parametric modelling; multiple-input multiple-output system; nonlinear system; parametric linear approaches; recursive least squares technique; system identification; twin rotor system; Genetic algorithms; Least squares methods; Nonlinear dynamical systems; Parametric statistics; Predictive models; Resonance light scattering; Rotors; System identification; Testing; Transmission line measurements;
Conference_Titel :
Control, Communications and Signal Processing, 2004. First International Symposium on
Print_ISBN :
0-7803-8379-6
DOI :
10.1109/ISCCSP.2004.1296232
