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- W4385452350 abstract "This study describes the difficulties that arise while fine-tuning the PID controllers. PID controllers are used in various systems to keep things stable but finding the right settings can be tricky, especially for complex systems that behave in unpredictable ways. If the controller has not been set up correctly, it can cause the system to become unstable and not perform as intended. Although there are some techniques that have shown promise in the past, they also have their limitations.To tackle this issue, this study proposes a solution that uses metaheuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Ant Colony Optimization (ACO). These algorithms are designed to find optimal settings for the controller more efficiently than traditional methods. The objective of this research is to compare how well these new methods are compared to the traditional methods. The results show that the new algorithms are more effective and lead to better performance and stability in the system. This research provides a promising solution to the challenges of fine-tuning PID controllers, especially for more complex systems that are difficult to control." @default.
- W4385452350 created "2023-08-02" @default.
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- W4385452350 date "2023-06-01" @default.
- W4385452350 modified "2023-09-26" @default.
- W4385452350 title "Tuning A PID Controller using Metaheuristic Algorithms" @default.
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- W4385452350 doi "https://doi.org/10.1109/icces57224.2023.10192687" @default.
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