Abstract
This paper is a discussion on a novel controller tuning method for the PID-based BBO method. The proposed approach had superior characteristics, including stable convergence characteristic, easy implementation, and good computational efficiency. From experimental results, the designed PID controllers-based BBO have less overshoot and short response time compared to that of the classical method. Therefore, BBO approach is taken as a better solution to improve the performance of the PID controller.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Asuntha A, Srinivasan A (2014) Intelligent PID controller tuning using PSO for linear system. Int J Innovative Sci Eng Technol 1(5):166–174
Visioli A (2001) Tuning of PID controllers with fuzzy logic. Proc Inst Elect Eng Contr Theory Appl 148(1):1–8
Seng TL, Khalid MB, Yusof R (1999) Tuning of a neuro-fuzzy controller by genetic algorithm. IEEE Trans Syst Man Cybern B 29:226–236
Solihin MI, Tack LF Kean ML (2011) Tuning of PID controller using particle swarm optimization (PSO). In: Proceeding of the international conference on advanced science, Malaysia, pp 458–461
Krohling RA, Rey JP (2001) Design of optimal disturbance rejection PID controllers using genetic algorithm. IEEE Trans Evol Comput 5:78–82
Mitsukura Y, Yamamoto T, Kaneda M (1999) A design of self-tuning PID controllers using a genetic algorithm. In: Proceedings of American control conference, San Diego, CA, pp 1361–1365
Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 6(12):702–713
Simon D, Ergezer M, Dawei D (2009) Markov analysis of biogeography-based optimization. http://academic.csuohio.edu/simond/bbo
Simon D, Ergezer M, Dawei D (2009) Markov models for biogeography-based optimization and genetic algorithms with global uniform recombination. http://academic.csuohio.edu/simond/bbo/markov/MarkovJournal.pdf
Simon D (2009) A probabilistic analysis of a simplified biogeography-based optimization algorithm. http://academic.csuohio.edu/simond/bbo/simplified/bbosimplified.pdf
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Su, K., Chang, T., Zhu, B., Han, B. (2015). PID Tuning for LOS Stabilization System Controller Based on BBO Algorithm. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46463-2_54
Download citation
DOI: https://doi.org/10.1007/978-3-662-46463-2_54
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46462-5
Online ISBN: 978-3-662-46463-2
eBook Packages: EngineeringEngineering (R0)