Parametric modelling of a twin rotor system using genetic algorithms

International Symposium on Control, Communications and Signal Processing, ISCCSP

Volumn , Issue , 2004, Pages 115-118

  Mat Darus, I Z ^a   Aldebrez, F M ^a   Tokhi, M O ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Genetic algorithm; Parametric modelling; System identification; Twin rotor system

Indexed keywords

COMPUTER SIMULATION; CORRELATION METHODS; GENETIC ALGORITHMS; IDENTIFICATION (CONTROL SYSTEMS); LINEAR SYSTEMS; OPTIMIZATION; SYSTEMS ANALYSIS;

ONE-STEP-AHEAD (OSA) PREDICTION; PARAMETRIC MODELING; TWIN ROTOR SYSTEMS;

ROTORS;

EID: 3042606105     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Ljung, L. and Soderström, T. "Theory and Practice of Recursive Identification," MIT Press, Cambridge, 1983.
2. Vandersteen, G., Rolain, Y., Schoukens, J. and Pintelon, R. "On the use of system identification for accurate parametric modeling of nonlinear systems using noisy measurements", IEEE Transactions on Instrumentation and Measurement, 45, (2), pp 605-609, 1996.
3. Feedback Instruments Ltd., Twin Rotor MIMO System Manual 33-007-0, Sussex, UK, 1996.
4. Holland, J. H. "Adaptation in Natural and Artificial Systems ", University of Michigan Press, Ann Arbor, MI, 1975.
5. Chipperfield, A. J. and Fleming, P. J. (1994). Parallel Genetic Algorithms: A Survey, Research report no. 518, Department of Automatic Control and Systems Engineering, The University of Sheffield, UK.
6. Ahmad, S. M., "Modeling and Control of a Twin Rotor Multi-Input Multi-Output System," PhD Thesis, Department of Automatic Control and Systems Engineering, University of Sheffield, UK, 2001.