Design of PID Controllers by Bat Algorithm for Benchmark Systems
Keywords:
PID controllers, Benchmark Systems, Bat Algorithm, Artificial Intelligent SearchAbstract
This paper proposes a design of optimal proportional-integral-derivative (PID) controllers for benchmark systems by bat algorithm (BA), one of the most efficient artificial intelligent search techniques. The BA is based on the echolocation behaviour of micro bats with varying pulse emission and loudness. In this work, the BA is conducted to optimally design PID controller for benchmark systems proposes by K. J. Åström and T. Hägglund. As simulation results, it was found that the proposed BA-based PID design giving very satisfied performance for various designing PID controllers.
References
S. Bennett, “Development of the PID controller,” IEEE Control System Magazine, pp.58–65, 1994.
R. C. Dorf, “Modern Control Systems,” 10th edn. New Jersey Prentice-Hall, 2005.
J. G. Ziegler and N. B. Nichols, “Optimum Settings for Automatic Controllers,” Trans. ASME, vol. 64, pp. 759-768, 1942.
A. O. Dwyer, Handbook of PI and PID Controller Tuning Rules, Imperial College Press, 2003.
K. J. Åström and T. Hägglund, “Benchmark Systems for PID Control,” IFAC Digital Control: Past, Present and Future of PID Control, Terrassa, Spain, pp.165–166, 2000.
S. Mehrdad and C. Greg, “An Adaptive PID Controller based on Genetic Algorithm Processor,” Proc. IEE Conf. on Genetic Algorithm in Engineering System, pp. 88–93, 1995.
Y. Mitsukura, T. Yamamoto and M. Kaneda, “A Design of Self-tuning PID Controller using a Genetic Algorithm,” Proc. American Control Conference, pp. 1361–1365, 1999.
J. F. Whidborne, “A Genetic Algorithm Approach to Design Finite–Precision PID Controller
Structures,” Proc. American Control Conference, pp. 4338–4342, 1999.
X. S. Yang, “A new metaheuristic bat-inspired an algorithm,” in: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) (Eds. J. R. Gonzalez et al.), Studies in Computational Intelligence, Springer Berlin, 284, Springer, pp. 65–74, 2010. [10] X. S. Yang, “Bat algorithm for multi-objective optimization,” Int. J. Bio-Inspired Computation, vol. 3 no. 5, pp. 267–274, 2011.
P. W. Tsai, J. S. Pan, B. Y. Liao, M. J. Tsai, and V. Istanda, “Bat algorithm inspired algorithm for solving numerical optimization problems,” Applied Mechanics and Materials, vol. 148–149, pp. 134–137, 2011.
MATLAB/SIMULINK User’s Guide, The Math Works Inc., Natick, MA, 1998.
Downloads
Published
How to Cite
Issue
Section
License
1. Every article published must be considered academic quality from 3 peers review experts per article.
2. The text or comments in this issue of science, technology and innovation journals belong to the author of the article. The journal organizers do not need to agree.
3. The editorial department of Science, Technology and Innovation Journal does not claim copy rights but provides references.
