Artificial Bee Colony Optimization Algorithm with Flexible Manipulator System

Authors

  • Jin Yao Lee
  • Mohd Ruzaini Hashim
  • M. O. Tokhi

Abstract

This paper presents the Artificial Bee Colony (ABC) optimization algorithm with application to flexible manipulator system (FMS). The aim of the algorithm is to find the best possible tuning parameter that can provide accurate angle trajectory of FMS. Five performance criteria have been used as an objective function of this problem where several conditions with different ABC parameters setting are set to determine which performance criteria is most suitable in tuning the PID controller in order to obtain the best FMS performance. The results show that the ABC with Root Mean Square Error (RMSE) as performance criteria outperforms the ABC with other performance criteria and it able to tune the PID controller of FMS to the desired hub angle trajectory.

References

G. Zhu and S. Kwong, “Gbest-guided artificial bee colony algorithm for numerical function optimization,” Appl. Math. Comput., vol. 217, no. 7, pp. 3166–3173, 2010.

C. Zhang, D. Ouyang, and J. Ning, “An artificial bee colony approach for clustering,” Expert Syst. Appl., vol. 37, no. 7, pp. 4761–4767, 2010.

M. R. Hashim, A. K. Hyriel, M. O. Tokhi, “Optimal tuning of PD controllers using modified artificial bee colony algorithm,” Journal of Telecommunocation,Electronic and Computer Engineering, vol. 10, no. 2-8, p. 67-70, 2018.

E. Dilmen, S. Yilmaz, and S. Beyhan, An Intelligent Hybridization of ABC and LM Algorithms With Constraint Engineering Applications, 1st ed. Elsevier Inc., 2017.

Z. Ye, Z. Hu, H. Wang, and H. Chen, “Automatic threshold selection based on artificial bee colony algorithm,” 2011 3rd Int. Work. Intell. Syst. Appl. ISA 2011 - Proc., 2011.

S. Sukpancharoen, T. R. Srinophakun, and J. Hirunlabh, “The application of a mixed coding approach to address mixed integer linear and non-linear programming problems using Particle Swarm Optimization (PSO) with an Artificial Bee Colony (ABC) Algorithm,” ACM Int. Conf. Proceeding Ser., pp. 78–83, 2018.

D. W. Lim, E. H. Kim, and Y. K. Lee, “Anti-vibration PID control for a robot manipulator experiments,” URAI 2011 - 2011 8th Int. Conf. Ubiquitous Robot. Ambient Intell., pp. 724–726, 2011.

Z. Mohamed, J. M. Martins, M. O. Tokhi, J. Sá da Costa, and M. A. Botto, “Vibration control of a very flexible manipulator system,” Control Eng. Pract., vol. 13, no. 3, pp. 267–277, 2005.

B. A. Md Zain, M. O. Tokhi, and S. F. Toha, “PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation,” EMS 2009 - UKSim 3rd Eur. Model. Symp. Comput. Model. Simul., pp. 355–360, 2009.

M. R. Hashim and M. O. Tokhi, "Greedy spiral dynamic algorithm with application to controller design," 2016 IEEE Conference on Systems, Process and Control (ICSPC), Bandar Hilir, 2016, pp. 29-32.

M. O. Sharma, S. K. and Tokhi, “Dynamic modelling of a flexible manipulator,” Proc. 2000JUSFA ASME 2000 Japan-USA Symp. Flex. Autom. 23-26 July, vol. 19, no. 4, p. CDROM, 2000.

M. Zulhilmi, “VIBRATION CONTROL OF SINGLE LINK FLEXIBLE MANIPULATOR BY USING NEURAL NETWORK,” no. June, 2013.

K. S. Rao and R. Mishra, “Comparative study of P, PI and PID controller for speed control of VSI-fed induction motor,” vol. 2, no. 2, pp. 2740–2744, 2014.

K. Krishnan and G. Karpagam, “Comparison of PID Controller Tuning Techniques for a FOPDT System,” Int. J. Curr. Eng. Technol., vol. 4, no. 4, pp. 2667–2670, 2014.

Downloads

Published

2020-10-30

How to Cite

Yao, L. J., Hashim, M. R., & M. O. Tokhi. (2020). Artificial Bee Colony Optimization Algorithm with Flexible Manipulator System. International Journal of Electrical Engineering and Applied Sciences (IJEEAS), 3(2). Retrieved from https://ijeeas.utem.edu.my/ijeeas/article/view/5985