Parametric Modelling of a Flexible Plate Structure Using Artificial Immune System Algorithm

  • Authors:

  • S. M. Salleh;M. O. Tokhi

  • Affiliations:

  • Department of Automatic Control and Systems Engineering, The University of Sheffield Email: cop07sbm@sheffield.ac.uk, United Kingdom;Department of Automatic Control and Systems Engineering, The University of Sheffield Email: cop07sbm@sheffield.ac.uk, United Kingdom

  • Venue:
  • ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Parametric modelling of dynamic systems may benefit from advantages of biologically-inspired immune system, which maintains its own system against dynamically changing environments through the interaction between lymphocytes and/or antibodies. In this paper, artificial immune system with clonal selection algorithm and artificial immune network are used to identify the unknown parameters characterising a flexible plate system. The identification is performed on basis of minimising the mean-squared output error and is assessed with correlation tests and in time and frequency domains. The approach is tested with three different disturbance signals. Simulation results demonstrate the potential of artificial immune system as promising technique with fast convergence and less computational time in comparison to binary-coded genetic algorithm.