Improvement of PID Algorithm by Fuzzy Control: Comparative And Analysis

DOI

10.2991/978-94-6463-518-8_51How to use a DOI?

Keywords

Fuzzy Control; PID Control; Falstad; MATLAB

Abstract

This study addresses the challenge of enhancing conventional PID control algorithms to cope wit h the complexities of modern industrial systems, characterized by significant interference and errors. Despite its long history and widespread use, PID control has limitations in such contexts. The primary goal is to investigate how integrating fuzzy control techniques can improve the performance of traditional PID algorithms. Fuzzy control is seen as a more advanced strategy capable of handling complex systems effectively. The study conducts a thorough literature review to understand previous research in fuzzy control. Simulation tools like Falstad and MATLAB are then utilized to compare PID and fuzzy control algorithms in controlling DC motors, with mathematical models and simulation circuits for validation. Simulation outcomes demonstrate that integrating fuzzy control with PID algorithms leads to faster convergence towards target values and improved stability, particularly in complex systems like DC motors.While traditional PID controllers are widely used for their simplicity, this study suggests that incorporating fuzzy control techniques can enhance their performance in managing higher-level system control tasks. Moreover, it hints at the potential of integrating AI technologies, such as deep learning algorithms, to further refine traditional control methodologies, advancing industrial automation efficiency and adaptability.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yinghan Leng
PY  - 2024
DA  - 2024/09/28
TI  - Improvement of PID Algorithm by Fuzzy Control: Comparative And Analysis
BT  - Proceedings of the 2024 International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2024)
PB  - Atlantis Press
SP  - 544
EP  - 557
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-518-8_51
DO  - 10.2991/978-94-6463-518-8_51
ID  - Leng2024
ER  -