Real-coded Genetic Algorithm Identification of a Flexible Plate System

Parametric modelling deals with determination of model parameters of a system. Parametric modelling of systems may benefit from advantages of real coded genetic algorithms (RCGAs), as they do not suffer from loss of precision during the processes of encoding and decoding compared with Binary Coded Genetic Algorithm. In this paper, RCGA is used to identify the best model order and associated parameters characterising a thin plate system. The performance of the approach is assessed on basis mean-squared error, time and frequency domain response of the developed model in characterising the system. A comparative assessment of the approach with binary coded GA is also provided. Simulation results signify the advantages of RCGA over two further algorithms in modelling the plate system are also provided.