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Issue title: Artificial Intelligent Techniques and its Applications
Guest editors: Mahalingam Sundhararajan, Xiao-Zhi Gao and Hamed Vahdat Nejad
Article type: Research Article
Authors: Ding, Bi-Rong | Qu, Xin-Huai; * | Chen, Yuan-Long
Affiliations: School of Machinery Engineering, Hefei University of Technology, Hefei, Anhui, China
Correspondence: [*] Corresponding author. Xin-Huai Qu, School of Machinery Engineering, Hefei University of Technology, Hefei, Anhui 230009, China. E-mail: dpf226681@126.com.
Abstract: Genetic algorithm is a kind of algorithm which applies the theory of natural evolution to search. In the process of mechanical design, genetic algorithm or improved genetic algorithm has become a hot research topic. In this paper, with the advantages of nonlinear genetic algorithm, the kinematic performance of planar five bar linkage was optimized. The objective function was defined as the Jacobi number of the parallel mechanism, which solved the optimization problem of the rod length. According to the optimized length of the five bar mechanism, kinematics simulation was carried out in MATLAB, and the trajectory of the third joints of the five-bar mechanism was optimized. According to the calculation results, the Jacobi condition number of five bar mechanism was compared. The results show that the proposed algorithm can effectively improve the performance of five bar mechanism, so the effect of genetic algorithm on mechanical optimal design is proved.
Keywords: Linkage mechanism, trajectory optimization, genetic algorithm, Jacobian condition number, kinematics simulation
DOI: 10.3233/JIFS-169380
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 2, pp. 871-878, 2018
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