Optimizing central pattern generators (CPG) controller for one legged hopping robot by using genetic algorithm (GA)

  • Authors

    • Arman Hadi Azahar
    • Chong Shin Horng
    • Anuar Mohamed Kassim
    • Amar Faiz Zainal Abidin
    • Mohamad Haniff Harun
    • Mohd Badril Nor Shah
    • Khalil Azha Mohd Annuar
    • Mustafa Manap
    • Zairi Ismael Rizman

    How to Cite

    Hadi Azahar, A., Shin Horng, C., Mohamed Kassim, A., Faiz Zainal Abidin, A., Haniff Harun, M., Badril Nor Shah, M., Azha Mohd Annuar, K., Manap, M., & Ismael Rizman, Z. (2018). Optimizing central pattern generators (CPG) controller for one legged hopping robot by using genetic algorithm (GA). International Journal of Engineering and Technology, 7(2.14), 160-164. https://doi.org/10.14419/ijet.v7i2.14.12817

    Received date: May 14, 2018

    Accepted date: May 14, 2018

    Published date: April 6, 2018

    https://doi.org/10.14419/ijet.v7i2.14.12817
  • One Legged, Hopping, CPG, PI, Genetic Algorithm
  • Abstract

    This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA). To control the one legged hopping robot, a CPG controller is designed and integrated with a conventional Proportional-Integral (PI) controller. Conventionally, the CPG parameters are tuned manually. But by using this method, the parameters produced are not exactly the optimum parameters for the CPG. Therefore, a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. The GA is designed based on minimizing the error produced towards achieving the reference height. The re-sponse of the one legged hopping robot is compared and the results of the error towards reference height are analyzed.

     

     

  • References

    1. [1] Bauer C, Braun S, Chen Y, Jakob W & Mikut R (2006), Optimization of artificial central pattern generators with evolutionary algorithms. Proceedings of the 18th Workshop Computational Intelligence, pp. 40–54.

      [2] Larsen JC, Central pattern generators in modern science.

      [3] Matsuoka K (1985), Sustained oscillations generated by mutually inhibiting neurons with adaptation. Biological Cybernetics 52, 367–376.

      [4] Matsuoka K (1987), Mechanisms of frequency and pattern control in the neural rhythm generators. Biological Cybernetics 56, 345–353.

      [5] Taga G, Yamaguchi Y & Shimizu H (1991), Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment. Biological Cybernetics 65, 147–159.

      [6] Taga G (1992), Modeling and simulation of biped locomotion. Journal of Society of Biomechanism of Japan 16, 209–214.

      [7] Inada H & Ishii K (2004), Bipedal walk using a central pattern generator. International Congress Series 1269, 185–188.

      [8] Arena P (2001), a mechatronic lamprey controlled by analog circuits. Proceedings of the ninth IEEE Mediterranean Conference on Control and Automation.

      [9] Kassim AB & Yasuno T (2010), Moving control of quadruped hopping robot using adaptive CPG networks. Proceedings of the IEEE Conference on Robotics Automation and Mechatronics, pp. 581–588.

      [10] Rahim NH, Kassim AM, Miskon MF & Azahar AH (2011), Effectiveness of central pattern generator model on developed one-legged hopping robot. Proceedings of the IEEE Student Conference on Research and Development, pp. 85–88.

      [11] Azahar AH, Horng CS & Kassim AM (2013), Vertical motion control of a one legged hopping robot by using central pattern generator (CPG). Proceedings of the IEEE Symposium on Industrial Electronics and Applications, pp. 7–12.

      [12] Hooper SL (2001), Central pattern generator. https://pdfs.semanticscholar.org/521c/c0324b14160bbdb9e77c16877bda734a21ef.pdf.

      [13] Malhotra R, Singh N & Singh Y (2011), Genetic algorithms: Concepts, design for optimization of process controllers. Computer and Information Science 4, 39–54.

      [14] Karthikraja A, Petchinathan G & Ramesh S (2009), stochastic algorithm for PID tuning of bus suspension system. Proceedings of the IEEE International Conference on Control, Automation, Communication and Energy Conservation, pp. 1–6.

      [15] Vladu EE & Dragomir TL (2004), Controller tuning using genetic algorithms. Proceedings of the first Romanian-Hungarian Joint Symposium on Applied Computational Intelligence, pp. 1–10.

      [16] Chen Y, Bauer C, Burmeister O, Rupp R & Mikut R (2007), First steps to future applications of spinal neural circuit models in neuroprostheses and humanoid robots. Proceedings of the 17th Workshop Computational Intelligence, pp. 186–199.

  • Downloads

  • How to Cite

    Hadi Azahar, A., Shin Horng, C., Mohamed Kassim, A., Faiz Zainal Abidin, A., Haniff Harun, M., Badril Nor Shah, M., Azha Mohd Annuar, K., Manap, M., & Ismael Rizman, Z. (2018). Optimizing central pattern generators (CPG) controller for one legged hopping robot by using genetic algorithm (GA). International Journal of Engineering and Technology, 7(2.14), 160-164. https://doi.org/10.14419/ijet.v7i2.14.12817

    Received date: May 14, 2018

    Accepted date: May 14, 2018

    Published date: April 6, 2018