Levy Flight-Augmented Artificial Circulatory System Algorithm for optimal PID tuning in DC motor control
In this study, an artificial circulatory system algorithm (ACSA) integrated with Levy flight dynamics is proposed to determine the optimum PID parameters for DC motor speed control. The proposed Levy-ACSA (LF-ACSA) algorithm aims to overcome the local-optimality and exploration–exploitation imbalanc...
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| Vydané v: | International journal of electronics and communications Ročník 204; s. 156101 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier GmbH
01.01.2026
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| Predmet: | |
| ISSN: | 1434-8411 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | In this study, an artificial circulatory system algorithm (ACSA) integrated with Levy flight dynamics is proposed to determine the optimum PID parameters for DC motor speed control. The proposed Levy-ACSA (LF-ACSA) algorithm aims to overcome the local-optimality and exploration–exploitation imbalance problems of existing methods. The LF-ACSA method is compared with 7 metaheuristics on 23 classical benchmark functions and the CEC2022 problem set. It is also verified that LF-ACSA achieves the lowest fitness value according to the ITAE criterion in the evaluations using PID gains and thus shows a faster and more stable convergence performance. In addition, compared to similar methods in the literature, the proposed approach provides a more accurate and balanced response in terms of overshoot percentage, rise time and settling time, which are important performance metrics in control systems under nominal and disturbed system conditions. In the simulated DC motor scenario, it is observed that the LF-ACSA-PID controller offers the highest bandwidth and maintains stability in the open-loop frequency response. Moreover, in terms of load disturbances and disturbance rejection analysis, it empirically demonstrates that the proposed approach suppresses disturbance rapidly and effectively, returning the system to its nominal operating state with minimal deviation. While this work represents the first application of ACSA in control engineering, it provides a perspective on how Levy-based integration can improve the algorithm’s exploitation capability and opens the door to future extensions in advanced control structures. |
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| ISSN: | 1434-8411 |
| DOI: | 10.1016/j.aeue.2025.156101 |