Swarm intelligence for modeling a flexible plate structure system with clamped-clamped-free-free boundary condition edges

Abstract

This paper presents the performance of developed model for a flexible plate structure using swarm intelligence via artificial bee colony and particle swarm optimization algorithms. An experimental rig of rectangular flexible plate with clamped-clamped-free-free edges boundary condition was designed and fabricated in this research. Then, the data acquisition and instrumentation systems were integrated on the rig to collect the input-output vibration data of flexible plate. The rig was excited during conducting the experiment using piezoelectric patch actuator to generate vibration responses. Later, the input-output data will be used to develop the model in this study. All the developed models were validated via mean squares error, one step-ahead prediction and correlation tests. The performance of developed models via artificial bee colony and particle swarm optimization algorithms has been compared each others. The simulation results show that the particle swarm optimization algorithm performs better than artificial bee colony algorithm and can be efficiently employed to be used as a platform of controller development in the future.