Optimal Tuning of PD controllers using Modified Artificial Bee Colony Algorithm

M. R. Hashim, Hyreil A. K., M. O. Tokhi

Abstract


This paper presents an investigation of PD controller tuning using a modified artificial bee colony algorithm (MABC). The main purpose of this work is to apply and investigates the performance of MABC in tuning the PD controller of single link manipulator system (SLMS) in comparison with the original ABC. The objective of the MABC algorithm is to minimize the error by using mean square error (MSE) as an objective function. The proposed algorithm has also been tested in three benchmark functions with different dimensions to checked the robustness of the algorithm in different problems surface. The result shows that the MABC able to tune the controller to their best optimum value.

Keywords


Artificial Bee Colony; Local Search; Single Link Manipulator System, PD Controller;

Full Text:

PDF

References


T. Weise, “Global Optimization Algorithms–Theory and Application,” URL http//www. it-weise. de, Abrufdatum, vol. 1, p. 820, 2009.

L. J. Eshelman, R. A. Caruana, and J. D. Schaffer, “Biases in the crossover landscape,” Third Int. Conf. Genet. Algorithms, no. November 2014, pp. 10–19, 1989.

N. Muttil and S.-Y. Liong, “Superior Exploration–Exploitation Balance in Shuffled Complex Evolution,” J. Hydraul. Eng., vol. 130, no. 12, pp. 1202–1205, 2004.

T. Feng, Q. Xie, H. Hu, L. Song, C. Cui, and X. Zhang, “Bean Optimization Algorithm Based on Negative Binomial Distribution,” in Advances in Swarm and Computational Intelligence: 6th International Conference, ICSI 2015, held in conjunction with the Second BRICS Congress, CCI 2015, Beijing, China, June 25-28, 2015, Proceedings, Part I, Y. Tan, Y. Shi, F. Buarque, A. Gelbukh, S. Das, and A. Engelbrecht, Eds. Cham: Springer International Publishing, 2015, pp. 82–88.

I. Kassabalidis, M. a. El-Sharkawi, R. J. . I. Marks, P. Arabshahi, and A. A. Gray, “Swarm intelligence for routing in communication networks,” GLOBECOM’01. IEEE Glob. Telecommun. Conf. (Cat. No.01CH37270), vol. 6, pp. 3613–3617, 2001.

H. Garg, “Solving structural engineering design optimization problems using an artificial bee colony algorithm,” J. Ind. Manag. Optim., vol. 10, no. 3, pp. 777–794, 2013.

X. Yang, “Review of Meta-Heuristics and Generalised Evolutionary Walk Algorithm,” Int. J. Bio-Inspired Comput., vol. 3, no. 2, pp. 77–84, Apr. 2011.

R. Eberhart and J. Kennedy, “A new optimizer using particle swarm theory,” MHS’95. Proc. Sixth Int. Symp. Micro Mach. Hum. Sci., pp. 39–43, 1995.

D. Karaboga, B. Gorkemli, C. Ozturk, and N. Karaboga, “A comprehensive survey: artificial bee colony (ABC) algorithm and applications,” Artif. Intell. Rev., vol. 42, no. 1, pp. 21–57, Mar. 2012.

X. Yang and A. H. Gandomi, “Bat algorithm: a novel approach for global engineering optimization,” Eng. Comput., vol. 29, no. 5, pp. 464–483, 2012.

K. M. Passino, “Biomimicry of bacterial foraging for distributed optimization and control,” Control Syst. IEEE, vol. 22, no. 3, pp. 52– 67, 2002.

M. Dorigo, V. Maniezzo, and a Colorni, “The ant systems: optimization by a colony of cooperative agents,” IEEE Trans. Man, Mach. Cybern. B, vol. 26, no. 1, 1996.

X. Yang, Nature-Inspired Metaheuristic Algorithms Second Edition. 2010.

H. Shareef, M. M. Islam, A. A. Ibrahim, and A. H. Mutlag, “A Nature Inspired Heuristic Optimization Algorithm Based on Lightning,” 2015 3rd Int. Conf. Artif. Intell. Model. Simul., pp. 9–14, 2015.

Z. W. . Geem, J. H. . Kim, and G. V. . Loganathan, “A New Heuristic Optimization Algorithm: Harmony Search,” Simulation, vol. 76, no. 2, pp. 60–68, 2001.

Z. W. Geem, X. S. Yang, and C. L. Tseng, “Harmony search and nature-inspired algorithms for engineering optimization,” J. Appl. Math., vol. 2013, pp. 2–4, 2013.

H. Shah-Hosseini, “Principal Components Analysis by the Galaxy-Based Search Algorithm: a Novel Metaheuristic for Continuous Optimisation,” Int. J. Comput. Sci. Eng., vol. 6, no. 1/2, pp. 132–140, Jul. 2011.

K. Tamura and K. Yasuda, “Spiral dynamics inspired optimization,” J. Adv. Comput. Intell. Intell. Informatics, vol. 15, no. 8, pp. 1116– 1122, 2011.

M. R. Hashim and M. O. Tokhi, “Enhanced chaotic spiral dynamic algorithm with application to controller design,” in 2016 IEEE International Conference on Power and Energy (PECon), 2016, pp. 752–756.

M. R. Hashim and M. . O. Tokhi, “Greedy spiral dynamic algorithm with application to controller design,” in 2016 IEEE Conference on Systems, Process and Control (ICSPC), 2016, no. December, pp. 29– 32.

M. O. T. M.R. Hashim, “CHAOTIC SPIRAL DYNAMICS OPTIMIZATION ALGORITHM,” Adv. Coop. Robot. Proc. 19th Int. Conf. Clawar 2016, pp. 551–558, 2016.

karoboga, “basic idea on artificial bee colony algorithm,” 2005.

G. Li, P. Niu, and X. Xiao, “Development and investigation of efficient artificial bee colony algorithm for numerical function optimization,” Appl. Soft Comput. J., vol. 12, no. 1, pp. 320–332, 2012.

H. Supriyono, M. O. Tokhi, and B. a M. Zain, “Control of a singlelink flexible manipulator using improved bacterial foraging algorithm,” 2010 IEEE Conf. Open Syst. (ICOS 2010), no. Icos, pp. 68–73, Dec. 2010.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

ISSN: 2180-1843

eISSN: 2289-8131