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Lookup NU author(s): Dr Matthew Armstrong
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 by the authors. This article presents an in-depth analysis of three advanced strategies to tune fractional PID (FOPID) controllers for a nonlinear system of interconnected tanks, simulated using MATLAB. The study focuses on evaluating the performance characteristics of system responses controlled by FOPID controllers tuned through three heuristic algorithms: Ant Colony Optimization (ACO), Grey Wolf Optimizer (GWO), and Flower Pollination Algorithm (FPA). Each algorithm aims to minimize its respective cost function using various performance metrics. The nonlinear model was linearized around an equilibrium point using Taylor Series expansion and Laplace transforms to facilitate control. The FPA algorithm performed better with the lowest Integral Square Error (ISE) criterion value ((Formula presented.)) and faster convergence in constant values and fractional orders. This comprehensive evaluation underscores the importance of selecting the appropriate tuning strategy and performance index, demonstrating that the FPA provides the most efficient and robust tuning for FOPID controllers in nonlinear systems. The results highlight the efficacy of meta-heuristic algorithms in optimizing complex control systems, providing valuable insights for future research and practical applications, thereby contributing to the advancement of control systems engineering.
Author(s): Pazmino R, Pavon W, Armstrong M, Simani S
Publication type: Article
Publication status: Published
Journal: Algorithms
Year: 2024
Volume: 17
Issue: 7
Online publication date: 10/07/2024
Acceptance date: 06/07/2024
Date deposited: 05/08/2024
ISSN (electronic): 1999-4893
Publisher: MDPI
URL: https://doi.org/10.3390/a17070306
DOI: 10.3390/a17070306
Data Access Statement: Data are contained within the article.
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