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Article type: Research Article
Authors: Meng, Xiangzhong* | Ma, Ying | Guo, Qiang
Affiliations: Opto-Electronic Engineering College, Xi’an Technological University, Xi’an, Shaanxi, China
Correspondence: [*] Corresponding author: Xiangzhong Meng, Opto-Electronic Engineering College, Xi’an Technological University, Xi’an, Shaanxi 710021, China. E-mail: mxiangzhong@163.com.
Abstract: 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.
Keywords: Vibration control sensors and actuators cloud model QPSO, Chinese Library classification number O32 TB2 Document code A
DOI: 10.3233/JCM-215039
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 21, no. 5, pp. 1433-1440, 2021
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