| Summary: | Flexible structures are very much in demand in the aerospace, marine, civil engineering and robotics industries. Controlling unwanted vibrations on these flexible plate structures is very important to maintain the performance of the structures. To design and develop a good controller, the dynamics of the plate must be modelled adequately. This thesis presents the development of a dynamic characterization of a flexible plate structure using system identification techniques via evolutionary methods and a proportional-integral-derivative (PID) controller for vibration suppression of a flexible plate. Initially, a flexible plate experimental rig was designed and fabricated with a clamped-clamped-free-free (CCFF) boundary condition. Then, data acquisition and instrumentation system were designed and integrated with the rig. Several experimental procedures were conducted to acquire the input and output data of the flexible plate. The input-output data collected from experiments were utilized to develop the model of the system. Several parametric modeling approaches were devised using linear auto regressive with exogenous (ARX) model structure which included the least square (LS), recursive least square (RLS), genetic algorithm (GA) and particle swarm optimization (PSO) techniques. The developed models were validated using one step-ahead (OSA) prediction, mean squared error (MSE) and correlation tests. Amongst all, it was found that the LS algorithm performed better in terms of achieving the lowest MSE as compared to the RLS, GA and PSO performance. Besides, all developed models performed well in estimating the first mode of vibration which is the dominant mode of the structure. It was also found that GA based active vibration control (AVC) using auto tuning method is the best proposed controller for vibration suppression of flexible plate with CCFF edge boundary condition with the highest attenuation value obtained for the first mode of vibration is 112.93 dB.
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