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Complementary Learning Swarm Intelligence Based PID Antenna Position Control System with Disturbance Mitigation: A comparative Study
Subject area: Science,Engineering and Technology · Area of research: Control Engineering
DOI: https://doi.org/10.64388/IREV9I8-1718872
Abstract
This paper present a robust and efficient way of tuning PID controller using three variants of swam intelligence algorithms for disturbance attenuation, and control of a positioning system. While many tuning algorithms focuses on getting the best PID gains that will enable the system to track the command input, and little or no attention is paid on the effect of those gains on disturbance resulting from external natural and artificial sources. Out of the three variants considered, comprehensive learning particle swarm optimization (CLPSO) appear to be more promising in rapidly attenuating (mitigating) the effect of disturbance on the system with a maximum disturbance response amplitude of 0.000329, and peak overshoot of 0.00635 (0.635%), rise time of 0.01s, and setting time of 0.01s. The second most promising algorithm is toroidal bound CLPSO with disturbance response amplitude of 0.000518, and peak overshoot of 0.0812 (8.12%). These results depicts the robustness of swarm intelligence algorithm variants implemented, in combating the effects of external disturbance on the position-controlled system, and at the same time achieving a very low peak overshoot, rise time and settling time.
Keywords
Swarm Intelligent Algorithms, PID Controller, Disturbance Step Response, Ziegler–Nichols Tuning Method, Optimization, Objective Fitness Function.
References
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[2] I J Narath and M. Gopal: Control system Engineering, fourth Edition, 2006
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[4] Katsuhiko Ogata Modern Control Engineering Fifth Edition Upper Saddle River 3010
[5] K Smriti Rao, Ravi Mishra Comparative study of P, PI and PID controller for speed control of VSI-fed induction motor, International Journal of Engineering Development and Research, Volume 2, Issue 2, 2014
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How to cite this paper
@article{1718872,
author = {Sunday Iliya , Olurotimi Olakunle Awodiji, Geraldine Rangmoen Rimven},
title = {Complementary Learning Swarm Intelligence Based PID Antenna Position Control System with Disturbance Mitigation: A comparative Study},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {8},
pages = {2614-2619},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1718872.pdf},
abstract = {This paper present a robust and efficient way of tuning PID controller using three variants of swam intelligence algorithms for disturbance attenuation, and control of a positioning system. While many tuning algorithms focuses on getting the best PID gains that will enable the system to track the command input, and little or no attention is paid on the effect of those gains on disturbance resulting from external natural and artificial sources. Out of the three variants considered, comprehensive learning particle swarm optimization (CLPSO) appear to be more promising in rapidly attenuating (mitigating) the effect of disturbance on the system with a maximum disturbance response amplitude of 0.000329, and peak overshoot of 0.00635 (0.635%), rise time of 0.01s, and setting time of 0.01s. The second most promising algorithm is toroidal bound CLPSO with disturbance response amplitude of 0.000518, and peak overshoot of 0.0812 (8.12%). These results depicts the robustness of swarm intelligence algorithm variants implemented, in combating the effects of external disturbance on the position-controlled system, and at the same time achieving a very low peak overshoot, rise time and settling time.},
keywords = {Swarm Intelligent Algorithms, PID Controller, Disturbance Step Response, Ziegler–Nichols Tuning Method, Optimization, Objective Fitness Function.},
month = {February},
doi = {https://doi.org/10.64388/IREV9I8-1718872}
}