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Hexapod Robot Design and Performance Comparison of Fuzzy and PID Control Methods

Year 2020, Volume: 8 Issue: 1, 88 - 97, 31.01.2020

Levent Gökrem Mehmet Serhat Can Sefa Aydın

https://doi.org/10.17694/bajece.650784

Abstract

In this study, a six-leg spider robot
(hexapod) was designed and controlled for greenhouse, search and rescue
operations and military applications. Solidworks design program was used in the
design stage and Matlab Simulink program was used in the control stage of the
robot. In the study, a motion trajectory was determined by interpolation
technique for the robot and it was aimed to move on this trajectory.
Proportional-Integral-Differential (PID) controller and Fuzzy Logic Controller
(FLC) were used for the trajectory control of the robot. The robot walk
movements were applied in both control types with motion on flat ground, motion
on inclined ground, motion at different weights and different friction
coefficients. In the analysis studies, the total weight of the robot was taken
into consideration as 4kg. As a result of the analysis studies, it was observed
that this robot, which was designed and analyzed, followed a trajectory defined
by a mass of 4 kg with an error value of 1 mm on average. During the trajectory
tracking, it was found that the Fuzzy controller performs better than the PID
controller at the turning points of the reference trajectory curve of the
robot.

Keywords

Solidworks Matlab PID fuzzy logic simulink hexapod robot

References

  • [1] G. Gürgüze, İ. Türkoğlu. “Kullanım Alanlarına Göre Robot Sistemlerinin Sınıflandırılması.” Fırat Üniversitesi Müh. Bil. Dergisi 31(1), pp. 53-66, 2019.
  • [2] F. Tedeschi, G. Carbone. “Design Issues for Hexapod Walking Robots.” Robotics 2014, 3, pp. 181-206; doi:10.3390/robotics3020181
  • [3] D. Chàvez-Clemente. “Gait Optimization for Multi-legged Walking Robots, with Application to a Lunar Hexapod.” Ph.D. Thesis, Stanford University, California, CA, USA, 2011.
  • [4] G. Carbone, M. Ceccarelli. “Legged Robotic Systems. Cutting Edge Robotics” ARS Scientific Book, Vienna: pp. 553–576, 2005.
  • [5] S. E. Hamamci. “A New PID Tuning Method Based on Transient Response Control.” Balkan Journal of Electrical & Computer Engineering, Vol.2, No.3, 2014 pp 132-138.
  • [6] Caponetto, R., Fortuna, L., Porto, D. “Parameter Tuning of A Non-Integer Order PID Controller.” 15th International Symposium on Mathematical Theory of Networks and Systems, Notre Dame, Indiana, 2002.
  • [7] A. Ates, B. B. Alagoz, G.T. Alisoy, C. Yeroglu and H. Z. Alisoy, “Fuzzy Velocity and Fuzzy Acceleration in Fractional Order Motion.” Balkan Journal of Electrical & Computer Engineering, Vol 3, No 2, 2015, pp 98-102, DOI:10.17694/bajece.52354
  • [8] A. Sarabakha, C. Fu, E. Kayacan. “Intuitbeforetuning: Type-1 and type-2 fuzzy logic controllers.” Applied Soft Computing, Vol 81, 2019.https://doi.org/10.1016/j.asoc.2019.105495
  • [9] O. Castillo, L. Amador-Angulo, J.R. Castro, M. Garcia-Valdez, A comparativestudy of type-1 fuzzy logic systems, interval type-2 fuzzy logic systemsand generalized type-2 fuzzy logic systems in control problems, Inform.Sci. 354 (2016) 257–274, http://dx.doi.org/10.1016/j.ins.2016.03.026.
  • [10] L. Cervantes, O. Castillo. “Type-2 fuzzy logic aggregation of multiple fuzzycontrollers for airplane flight control.” Inform. Sci. 324 (2015) 247–256,http://dx.doi.org/10.1016/j.ins.2015.06.047.
  • [11] R.-E. Precup, H. Hellendoorn, “A survey on industrial applications of fuzzycontrol.” Comput. Ind. 62 (3) (2011) 213–226, http://dx.doi.org/10.1016/j.compind.2010.10.001.
  • [12] A. Celikyilmaz, I.B. Turksen. “Modeling Uncertainty with Fuzzy Logic: With Recent Theory and Applications.” first ed., Springer-Verlag Berlin Heidelberg, 2009, http://dx.doi.org/10.1007/978-3-540-89924-2.
  • [13] T. Kumbasar, H. Hagras. “Big Bang-Big Crunch optimization based interval type-2 fuzzy PID cascade controller design strategy.” Inform. Sci. 282 (2014) 277–295, http://dx.doi.org/10.1016/j.ins.2014.06.005.
  • [14] C. Fu, A. Sarabakha, E. Kayacan, C. Wagner, R. John, J.M. Garibaldi. “Input uncertainty sensitivity enhanced nonsingleton fuzzy logic controllers forlong-term navigation of quadrotor UAVs.” IEEE/ASME Trans. Mechatronic.

Year 2020, Volume: 8 Issue: 1, 88 - 97, 31.01.2020

Levent Gökrem Mehmet Serhat Can Sefa Aydın

https://doi.org/10.17694/bajece.650784

Abstract

References

  • [1] G. Gürgüze, İ. Türkoğlu. “Kullanım Alanlarına Göre Robot Sistemlerinin Sınıflandırılması.” Fırat Üniversitesi Müh. Bil. Dergisi 31(1), pp. 53-66, 2019.
  • [2] F. Tedeschi, G. Carbone. “Design Issues for Hexapod Walking Robots.” Robotics 2014, 3, pp. 181-206; doi:10.3390/robotics3020181
  • [3] D. Chàvez-Clemente. “Gait Optimization for Multi-legged Walking Robots, with Application to a Lunar Hexapod.” Ph.D. Thesis, Stanford University, California, CA, USA, 2011.
  • [4] G. Carbone, M. Ceccarelli. “Legged Robotic Systems. Cutting Edge Robotics” ARS Scientific Book, Vienna: pp. 553–576, 2005.
  • [5] S. E. Hamamci. “A New PID Tuning Method Based on Transient Response Control.” Balkan Journal of Electrical & Computer Engineering, Vol.2, No.3, 2014 pp 132-138.
  • [6] Caponetto, R., Fortuna, L., Porto, D. “Parameter Tuning of A Non-Integer Order PID Controller.” 15th International Symposium on Mathematical Theory of Networks and Systems, Notre Dame, Indiana, 2002.
  • [7] A. Ates, B. B. Alagoz, G.T. Alisoy, C. Yeroglu and H. Z. Alisoy, “Fuzzy Velocity and Fuzzy Acceleration in Fractional Order Motion.” Balkan Journal of Electrical & Computer Engineering, Vol 3, No 2, 2015, pp 98-102, DOI:10.17694/bajece.52354
  • [8] A. Sarabakha, C. Fu, E. Kayacan. “Intuitbeforetuning: Type-1 and type-2 fuzzy logic controllers.” Applied Soft Computing, Vol 81, 2019.https://doi.org/10.1016/j.asoc.2019.105495
  • [9] O. Castillo, L. Amador-Angulo, J.R. Castro, M. Garcia-Valdez, A comparativestudy of type-1 fuzzy logic systems, interval type-2 fuzzy logic systemsand generalized type-2 fuzzy logic systems in control problems, Inform.Sci. 354 (2016) 257–274, http://dx.doi.org/10.1016/j.ins.2016.03.026.
  • [10] L. Cervantes, O. Castillo. “Type-2 fuzzy logic aggregation of multiple fuzzycontrollers for airplane flight control.” Inform. Sci. 324 (2015) 247–256,http://dx.doi.org/10.1016/j.ins.2015.06.047.
  • [11] R.-E. Precup, H. Hellendoorn, “A survey on industrial applications of fuzzycontrol.” Comput. Ind. 62 (3) (2011) 213–226, http://dx.doi.org/10.1016/j.compind.2010.10.001.
  • [12] A. Celikyilmaz, I.B. Turksen. “Modeling Uncertainty with Fuzzy Logic: With Recent Theory and Applications.” first ed., Springer-Verlag Berlin Heidelberg, 2009, http://dx.doi.org/10.1007/978-3-540-89924-2.
  • [13] T. Kumbasar, H. Hagras. “Big Bang-Big Crunch optimization based interval type-2 fuzzy PID cascade controller design strategy.” Inform. Sci. 282 (2014) 277–295, http://dx.doi.org/10.1016/j.ins.2014.06.005.
  • [14] C. Fu, A. Sarabakha, E. Kayacan, C. Wagner, R. John, J.M. Garibaldi. “Input uncertainty sensitivity enhanced nonsingleton fuzzy logic controllers forlong-term navigation of quadrotor UAVs.” IEEE/ASME Trans. Mechatronic.
There are 14 citations in total.

Details

Primary Language English
Subjects Electrical Engineering
Journal Section Araştırma Articlessi
Authors

Levent Gökrem 0000-0003-2101-5378

Mehmet Serhat Can 0000-0003-2356-9921

Sefa Aydın 0000-0001-9965-2903

Publication Date January 31, 2020
Published in Issue Year 2020 Volume: 8 Issue: 1

Cite

APA Gökrem, L., Can, M. S., & Aydın, S. (2020). Hexapod Robot Design and Performance Comparison of Fuzzy and PID Control Methods. Balkan Journal of Electrical and Computer Engineering, 8(1), 88-97. https://doi.org/10.17694/bajece.650784
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