Advances in Computational Design

Techno-Press (테크노프레스)
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Synthesis of four-bar linkage motion generation using optimization algorithms

  • Phukaokaew, Wisanu (Sustainable and Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, KhonKaen University) ;
  • Sleesongsom, Suwin (Department of Aeronautical Engineering, International Academy of Aviation Industry, King Mongkut's Institute of Technology Ladkrabang) ;
  • Panagant, Natee (Sustainable and Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, KhonKaen University) ;
  • Bureerat, Sujin (Sustainable and Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, KhonKaen University)
  • Received : 2018.05.27
  • Accepted : 2019.01.13
  • Published : 2019.07.25
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Abstract

Motion generation of a four-bar linkage is a type of mechanism synthesis that has a wide range of applications such as a pick-and-place operation in manufacturing. In this research, the use of meta-heuristics for motion generation of a four-bar linkage is demonstrated. Three problems of motion generation were posed as a constrained optimization probably using the weighted sum technique to handle two types of tracking errors. A simple penalty function technique was used to deal with design constraints while three meta-heuristics including differential evolution (DE), self-adaptive differential evolution (JADE) and teaching learning based optimization (TLBO) were employed to solve the problems. Comparative results and the effect of the constraint handling technique are illustrated and discussed.

Keywords

Acknowledgement

Supported by : Thailand Research Fund

References

  1. Acharyya, S.K. and Mandal, M. (2009), "Performance of EAs for four-bar linkage synthesis", Mech. Mach. Theory, 85, 1784-1794. https://doi.org/10.1016/j.mechmachtheory.2009.03.003.
  2. Baluja, S. (1994), "Population-based incremental learning: a method for integrating genetic search based function optimization and competitive learning", CMU-CS-95-163; Carnegie Mellon University, USA.
  3. Ebrahimi, S. and Payvandy, P. (2015), "Efficient constrained synthesis of path generating four-bar mechanisms based on the heuristic optimization algorithms", Mech. Mach. Theory, 85, 189-204. https://doi.org/10.1016/j.mechmachtheory.2014.11.021.
  4. Mirjalili, S., Mirjalili, S.M. and Lewis, A. (2014). "Grey wolf optimizer", Adv. Eng. Softw, 69, 46-61. https://doi.org/10.1016/j.advengsoft.2013.12.007.
  5. Mutawe, S.K., Al-Smadi, Y.M. and Sodhi, R.S. (2012), "Designing four-bar linkages for path generation with worst case joint clearances", Eng. Lett., 20(2), 143-147.
  6. Myszka, D.H. (2005), Machines and Mechanisms: Applied Kinematic Analysis, (3rd Edition), Prentice Hall, New Jersey, USA.
  7. Peng, C. (2010), "Optimal synthesis of planar adjustable mechanism", Ph.D. Dissertation, New Jersey Institute of Technology, New Jersey, USA.
  8. Rao, R.V. and Patel, V. (2012), "An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems", Sci. Iran. D, 20(3), 710-720. https://doi.org/10.1016/j.scient.2012.12.005.
  9. Shaheen, A.M., Spea, S.R., Farrag, S.M. and Abido, M.A. (2015), "A review of meta-heuristic algorithms for reactive power planning problem", Ain Shams Eng. J., 9(2), 215-231. https://doi.org/10.1016/j.asej.2015.12.003.
  10. Sleesongsom, S. and Bureerat S. (2018), "Alternative constraint handling technique for four-bar linkage path generation", IOP Conf. Series: Mater. Sci. Eng., 324, https://doi.org/10.1088/1757-899X/324/1/012012.
  11. Sleesongsom, S. and Bureerat, S. (2015), "Morphing wing structural optimization using opposite-based population-based incremental learning and multigrid ground elements", Math. Probl. Eng., 2015, http://dx.doi.org/10.1155/2015/730626.
  12. Sleesongsom, S. and Bureerat, S. (2015), "Optimal synthesis of four-bar linkage path generation through evolutionary computer", Res. Appl. Mech. Eng., 3(2), 46-53. https://doi.org/10.1155/2018/5462563.
  13. Sleesongsom, S. and Bureerat, S. (2017), "Four-bar linkage path generation through self-adaptive population size teaching-learning based optimization", Knowl.-Based Syst., 135, 180-191. https://doi.org/10.1016/j.knosys.2017.08.012.
  14. Storn, R.M. and Price, K.V. (1997), "Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces", J. Global Optim, 11, 341-359. https://doi.org/10.1023/A:1008202821328.
  15. Tong, Y., Myszka, D.H. and Murray, A.P. (2013), "Four-bar linkage synthesis for a combination of motion and path-point generation", ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Oregon, USA, August.
  16. Yu, H.Y., Zhao, Y.W., and Wang, Z.X. (2013), "Study on numerical comparison method of four-bar straightline guidance mechanism", J. Harbin Inst. Technol., 20, 63-72.
  17. Zhang, J. and Sanderson, A.C. (2009), "JADE: adaptive differential evolution with optional external archive", IEEE Transaction on Evol. Comp., 13(5), 945-958. https://doi.org/10.1109/TEVC.2009.2014613.

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