Hybrid clonal selection algorithm and the artificial bee colony algorithm for a variable PID-like fuzzy controller design

Jia Ping Tien, Tzuu Hseng S. Li

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

In this paper, a novel evolutionary learning algorithm is proposed by hybridizing the clonal selection algorithm (CLONALG) and the artificial bee colony algorithm (ABC). The algorithm is thus called HCABC to enhance the CLONALG performance. This algorithm presents a new idea to optimize the parameter and structure of the PID-like fuzzy controller simultaneously. The ABC algorithm has been proven to be very effective for solving global optimization. Hence, in the HCABC, the mutation mechanism of the CLONALG by using the advantages of ABC can improve the capabilities of exploration and ex-ploitation. Simulation results demonstrate that HCABC can effectively achieve the best PID-like fuzzy controller structure and parameters to a nonlinear and uncertainty control plant.

Original languageEnglish
Pages87-94
Number of pages8
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012 - Taichung, Taiwan
Duration: 2012 Nov 162012 Nov 18

Other

Other2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012
CountryTaiwan
CityTaichung
Period12-11-1612-11-18

Fingerprint

Clonal Selection Algorithm
Hybrid Algorithm
Fuzzy Controller
Controller Design
Evolutionary Learning
Global Optimization
Evolutionary Algorithms
Learning Algorithm
Mutation
Optimise
Uncertainty
Demonstrate

All Science Journal Classification (ASJC) codes

  • Logic

Cite this

Tien, J. P., & Li, T. H. S. (2012). Hybrid clonal selection algorithm and the artificial bee colony algorithm for a variable PID-like fuzzy controller design. 87-94. Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan. https://doi.org/10.1109/iFUZZY.2012.6409681
Tien, Jia Ping ; Li, Tzuu Hseng S. / Hybrid clonal selection algorithm and the artificial bee colony algorithm for a variable PID-like fuzzy controller design. Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan.8 p.
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Tien, JP & Li, THS 2012, 'Hybrid clonal selection algorithm and the artificial bee colony algorithm for a variable PID-like fuzzy controller design', Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan, 12-11-16 - 12-11-18 pp. 87-94. https://doi.org/10.1109/iFUZZY.2012.6409681

Hybrid clonal selection algorithm and the artificial bee colony algorithm for a variable PID-like fuzzy controller design. / Tien, Jia Ping; Li, Tzuu Hseng S.

2012. 87-94 Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan.

Research output: Contribution to conferencePaper

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N2 - In this paper, a novel evolutionary learning algorithm is proposed by hybridizing the clonal selection algorithm (CLONALG) and the artificial bee colony algorithm (ABC). The algorithm is thus called HCABC to enhance the CLONALG performance. This algorithm presents a new idea to optimize the parameter and structure of the PID-like fuzzy controller simultaneously. The ABC algorithm has been proven to be very effective for solving global optimization. Hence, in the HCABC, the mutation mechanism of the CLONALG by using the advantages of ABC can improve the capabilities of exploration and ex-ploitation. Simulation results demonstrate that HCABC can effectively achieve the best PID-like fuzzy controller structure and parameters to a nonlinear and uncertainty control plant.

AB - In this paper, a novel evolutionary learning algorithm is proposed by hybridizing the clonal selection algorithm (CLONALG) and the artificial bee colony algorithm (ABC). The algorithm is thus called HCABC to enhance the CLONALG performance. This algorithm presents a new idea to optimize the parameter and structure of the PID-like fuzzy controller simultaneously. The ABC algorithm has been proven to be very effective for solving global optimization. Hence, in the HCABC, the mutation mechanism of the CLONALG by using the advantages of ABC can improve the capabilities of exploration and ex-ploitation. Simulation results demonstrate that HCABC can effectively achieve the best PID-like fuzzy controller structure and parameters to a nonlinear and uncertainty control plant.

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Tien JP, Li THS. Hybrid clonal selection algorithm and the artificial bee colony algorithm for a variable PID-like fuzzy controller design. 2012. Paper presented at 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan. https://doi.org/10.1109/iFUZZY.2012.6409681