Modelling and control of horizontal flexible plate using particle swarm optimization

2018 ◽  
Vol 7 (2.29) ◽  
pp. 13
Author(s):  
Muhamad Sukri Hadi ◽  
Hanim Mohd Yatim ◽  
Intan Zaurah Mat Darus

This paper presents the modeling and active vibration control using an evolutionary swarm algorithm known as particle swarm optimization. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges as boundary conditions constrained at horizontal position. The purpose of the experimental rig development is to collect the input-output vibration data. Next, the data acquisition and instrumentation system were designed and integrated with the experimental rig. Several procedures were conducted to acquire the input-output vibration data. The collected vibration data were then utilized to develop the system model. The parametric modeling using particle swarm optimization was devised using an auto regressive model with exogenous model structure. The developed model was validated using mean square error, one step ahead prediction, correlation tests and pole-zero diagram stability. Then, the developed model was used for the development of controller using an active vibration control technique. It was found that particle swarm optimization based on the active vibration control using Ziegler-Nichols method has successfully suppressed the unwanted vibration of the horizontal flexible plate system. The developed controller achieved the highest attenuation value at the first mode of vibration which is the dominant mode in the system with 34.37 dB attenuation. 

Author(s):  
Xiangzhong Meng ◽  
Ying Ma ◽  
Qiang Guo

The adaptive quantum particle swarm optimization algorithm based on cloud model and the multi-island genetic algorithm [15] have obvious advantages in convergence speed to solve the sensor optimization problem, and can effectively achieve global optimization. Due to the installation of sensors and actuators, the electromechanical coupling coefficient of intelligent structures is changed, which affects the vibration energy of structures. In this paper, the reserved energy index of structural vibration control system is taken as the objective optimization function. The position, number, length and control gain of sensors and actuators of active vibration control system are optimized. The adaptive Quantum-behaved Particle Swarm Optimization algorithm in cloud model(CMQPSO) is used as the optimization strategy, and the cantilever beam is taken as an example. This approach is verified its effectiveness and feasibility. It is found that excellent optimization results are obtained.


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