Genetic algorithm-based identification of transfer function parameters for a rectangular flexible plate system

Authors:
Ali Reza Tavakolpour;Intan Z. Mat Darus;Osman Tokhi;Musa Mailah
Affiliations:
Department of Applied Mechanics, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor Bahru, Malaysia;Department of Applied Mechanics, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor Bahru, Malaysia;Department of Automatic Control and System Engineering, University of Sheffield, United Kingdom;Department of Applied Mechanics, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor Bahru, Malaysia
Venue:
Engineering Applications of Artificial Intelligence
Year:
2010

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Abstract

This paper focuses on an identification technique based on genetic algorithms (GAs) with application to rectangular flexible plate systems for active vibration control. A real coded GA with a new truncation-based selection strategy of individuals is developed, to allow fast convergence to the global optimum. A simulation environment characterizing the dynamic behavior of a flexible rectangular plate system is developed using the central finite difference (FD) techniques. The plate thus developed is excited by a uniformly distributed random disturbance and the input-output data of the system acquired is used for black-box modeling the system with the GA optimization using an autoregressive model structure. Model validity tests based on statistical measures and output prediction are carried out. The prediction capability of the model is further examined with unseen data. It is demonstrated that the GA gives faster convergence to an optimum solution and the model obtained characterizes the dynamic system behavior of the system well.