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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Bibliographic Details
Main Author: Gonzalez, Emmanuel A.
Format: text
Language:English
Published: Animo Repository 2006
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Online Access: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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Institution: De La Salle University
Language: English
Description
Summary: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.