Synthesis of a Hybrid Five-Bar Mechanism with Particle Swarm Optimization Algorithm

  • Authors:

  • Ke Zhang

  • Affiliations:

  • School of Mechanical and Automation Engineering, Shanghai Institute of Technology, Shanghai, China 200235

  • Venue:
  • ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
  • Year:
  • 2008

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Abstract

Hybrid mechanism is a new type of mechanism with flexible transmission behavior. Hybrid five-bar mechanism is the most representative one of them. In this paper, modeling and analysis for a hybrid five-bar mechanism based on power bond graph theory is introduced. An optimal dimensional synthesis of hybrid mechanism is performed with reference to dynamics objective function. Compared with conventional optimum evaluation methods such as simplex search and Powell method, Particle Swarm Optimization (PSO) algorithm can improve the efficiency of searching in the whole field by gradually shrinking the area of optimization variable. Compared to GA, PSO is easy to implement and there are few parameters to adjust. In order to solve the synthesis problem, integrating PSO optimization algorithm and MATLAB Optimization Toolbox for the constraint equations. Optimum link dimensions are obtained assuming there are no dimensional tolerances or clearances. Finally, a numerical example is carried out, and the simulation results show that the optimization method is feasible and satisfactory for hybrid mechanism.