Ant colony-based solutions for sub-optimal control systems
This study presents the design and development of a set of metaheuristics based on ant colony optimization for optimizing a feedback control system. The metaheuristics developed are based on the sequential attack of ants in the search space, which is then called Sequential Update-Based Ant Colony Op...
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| 格式: | text |
| 語言: | English |
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Animo Repository
2006
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| 在線閱讀: | https://animorepository.dlsu.edu.ph/etd_masteral/3446 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10284/viewcontent/CDTG004196_P.pdf |
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| 機構: | De La Salle University |
| 語言: | English |
| 總結: | This study presents the design and development of a set of metaheuristics based on ant colony optimization for optimizing a feedback control system. The metaheuristics developed are based on the sequential attack of ants in the search space, which is then called Sequential Update-Based Ant Colony Optimization (SeqACO). These metaheuristics are used in hybrid with different conventional PID tuning techniques in order to further optimize the feedback control system. Experimental and numerical results prove that a sequential update-based ant colony optimization metaheuristic can be developed and be used to solve combinatorial optimization problems, especially, PID tuning problems. |
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