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

研究成果: Paper

4 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁面87-94
頁數8
DOIs
出版狀態Published - 2012 十二月 1
事件2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012 - Taichung, Taiwan
持續時間: 2012 十一月 162012 十一月 18

Other

Other2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012
國家Taiwan
城市Taichung
期間12-11-1612-11-18

All Science Journal Classification (ASJC) codes

  • Logic

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