Optimal Tuning of Robust Controller Based on Artificial Bee Colony Algorithm

Abstract:

Artificial bee colony algorithm (ABCA) is a novel swarm intelligence algorithm for global optimization. An efficient method based on ABCA is proposed for optimal tuning of robust proportional-integral-derivative (PID) controller in this paper. A multi-objective optimization is applied to balance several constraint factors of controller. Performance of robust PID controller is evaluated by a three-order and time-delay transfer function with 40%, 50% and 60% uncertainty, respectively. Simulation result clearly demonstrates that the designed controller can obtain an optimal tuning and endure parameter fluctuation. From comparisons of robust PID controller in different uncertainties, a conclusion can be obtained that performance of robust PID controller will be worse as the uncertainty increases, even obtain a divergent solution when the uncertainty is more than 60%.

• Periodical: Advanced Materials Research (Volumes 562-564)
• Pages: 1668-1672
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.562-564.1668
• Online since: August 2012
• Authors: Kun Xu, Ming Yan Jiang
• Keywords: Artificial Bee Colony Algorithm (ABC), Design of Robust Controller, Multi-Objective Optimization (MOP), Optimal Tuning, PID Controller

References

[1] Liu-Hsu Lin, Fu-Cheng Wang and Jia-Yush Yen: Robust PID Controller Design Using Particle Swarm Optimization (Proceedings of the 7th Asian Control Conference, Hong Kong China, 2009), pp.1673-1678.

[2] Danica Rosinová and Vojtech Veselý: Robust PID Controller Design Using BMI (International Conference devoted to 150 Anniversary of Alexander Popov 2009), pp.896-901.

[3] Masanobu Obika and Toru Yamamoto: An Evolutionary Design of Robust PID Controllers (Proceedings of the IEEE International Conference on Mechatronics & Automation Niagara Falls, Canada 2005), pp.101-106.

DOI: 10.1109/icma.2005.1626530

[4] Ozden ERCIN and Ramazan COBAN: Comparison of the Artificial Bee Colony and the Bees Algorithm for PID Controller Tuning (Innovations in Intelligent Systems and Application(INISTA), Istanbul Turkey 2011) , pp.595-598.

DOI: 10.1109/inista.2011.5946157

[5] Anan Banhasakun, Tiranee Achalakul and Booncharoen Sirinaovakul: ABC-GSX: A hybrid method for solving the Traveling Salesman Problem (Second World Congress on Nature and Biologically Inspired Computing, Japan 2010) , pp.7-12.

DOI: 10.1109/nabic.2010.5716308

[6] Xiaoya Cheng and Mingyan Jiang: Cognitive Radio Spectrum Assignment Based on Artificial Bee Colony Algorithm (The IEEE International conference on communication technology (IEEE ICCT), Jinan China 2011), pp.1-4.

DOI: 10.1109/icct.2011.6157854

[7] Tirimula Rao Benala and Sree Durga Jampala: A novel Approach to Image Edge Enhancement Using Artificial Bee Colony Optimization Algorithm for Hybridized Smoothening Filters (World Congress on Nature & Biologically Inspired Computing (NaBIC), India 2009), pp.1071-1076.

DOI: 10.1109/nabic.2009.5393866

[8] Ma Longhua, Zheng Yongling and Qian Jixin: A New Hybrid Genetic Algorithm for Global Minimax Optimization (Info-tech and Info-net, 2001), pp.316-322.

DOI: 10.1109/icii.2001.983838