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.
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References
Mohd Hashim, S.Z., Tokhi, M.O., Mat Darus, I.Z.: Active vibration control of flexible structures using genetic optimisation. Journal of low frequency noise, vibration and active control 3(25), 195–207 (2006)
Alam, M.S., Tokhi, M.O.: Modelling and vibration control of a twin rotor system: a particle swarm optimisation approach. In: 13th International Congress on Sound and Vibration, Vienna, Austria (2006)
Mat Darus, I.Z., Tokhi, M.O.: Parametric modeling of a flexible 2D structure. Journal of low frequency noise, vibration and active control 23(2), 115–131 (2004)
de Castro, L., Von Zuben, F.J.: The Clonal Selection Algorithm with Engineering Applications. In: Proceedings of GECCO 2000, Workshop on Artificial Immune Systems and Their Applications (2000)
Jui-Yu, W., Yun-Kung, C.: Artificial immune system for solving generalized geometric problems: a preliminary results. In: Proceedings of the 2005 conference on Genetic and evolutionary computation. ACM, Washington (2005)
Malim, M.R., Khader, A.T., Mustafa, A.: Artificial Immune Algorithms for University Timetabling. In: The 6th International Conference on the Practice and Theory of Automated Timetabling. Masaryk University, Brno (2006)
Timoshenko, S., Woinowsky-Krieger, S.: Theory of plates and shells. McGraw-Hill Book Company, New York (1959)
Salleh, S.M., Tokhi, M.O.: Discrete simulation of flexible plate structure using state-space formulation. Journal of System Simulation 20(19), 5141–5146 (2008)
Simon, M.G.: How Do We Evaluate Artificial Immune Systems? Evolution Compution 13(2), 145–177 (2005)
de Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, Heidelberg (2002)
Burnet, F.M.: The Clonal Selection Theory of Acquired Immunity. Cambridge University Press, Cambridge (1959)
de Castro, L.N., Von Zuben, F.J.: aiNet: An Artificial Immune Network for Data Analysis. In: Abbass, H.A., Sarker, R.A., Newton, C.S. (eds.) Data Mining: A Heuristic Approach. Idea Group Publishing, USA (2001)
de Castro, L.N., Timmis, J.: An artificial immune network for multimodal function optimization. In: Proceedings of Evolutionary Computation Congress, CEC 2002 (2002)
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Salleh, S.M., Tokhi, M.O. (2009). Parametric Modelling of a Flexible Plate Structure Using Artificial Immune System Algorithm. In: Andrews, P.S., et al. Artificial Immune Systems. ICARIS 2009. Lecture Notes in Computer Science, vol 5666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03246-2_28
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DOI: https://doi.org/10.1007/978-3-642-03246-2_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03245-5
Online ISBN: 978-3-642-03246-2
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