Open AccessOptimization of anti-wind disturbance ability of a long-span cable-driven parallel camera robot based on a Genetic Algorithm
Author(s) -
Qing Zhu,
Yu Su,
Siqi Zhao
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2183/1/012018
Subject(s) - premature convergence , vibration , genetic algorithm , disturbance (geology) , computer science , control theory (sociology) , natural frequency , truncation (statistics) , engineering , algorithm , artificial intelligence , acoustics , geology , physics , paleontology , control (management) , machine learning
The cable-driven parallel camera robot is a long-span cable-supported high-rise structure, which is easy to produce vibration response due to wind disturbance, which affects its normal work. In this paper, the method of structural optimization is used to improve the first-order natural frequency of the system to keep it away from the energy truncation frequency, so as to reduce the wind-induced vibration response of the system. In order to avoid the defect of premature convergence of standard genetic algorithm, an adaptive multi-island genetic algorithm based on population information entropy is proposed for structure optimization. the simulation results show that the algorithm can more effectively improve the first-order natural frequency of the system and improve the wind disturbance resistance of the system.