A Comparative Study on Fuzzy Logic-Based Liquid Level Control Systems with Integrated Industrial Communication Technology
This study presents an advanced control system for liquid level regulation, comparing a traditional proportional-integral-derivative (PID) controller with a fuzzy logic controller. The system integrates a real-time monitoring and control interface, allowing flexible adjustments for research and trai...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/13/3/60 |
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| Summary: | This study presents an advanced control system for liquid level regulation, comparing a traditional proportional-integral-derivative (PID) controller with a fuzzy logic controller. The system integrates a real-time monitoring and control interface, allowing flexible adjustments for research and training applications. Unlike the PID controller, which relies on predefined tuning parameters, the fuzzy logic controller dynamically adjusts control actions based on system behavior, making it more suitable for processes with non-linear dynamics. The experimental results highlight the superior performance of the fuzzy logic controller over the PID controller. Specifically, the fuzzy logic controller achieved a 21% reduction in maximum overshoot, a 62% decrease in peak time, and an 83% reduction in settling time. These improvements demonstrate its ability to handle process fluctuations more efficiently and respond rapidly to changes in liquid levels. By offering enhanced stability and adaptability, the fuzzy logic controller presents a viable alternative for liquid level control applications. Furthermore, this research contributes to the development of flexible and high-performance control solutions that can be implemented in both industrial and educational settings. The proposed system serves as a cost-effective platform for hands-on learning in control system design, reinforcing contemporary engineering education and advancing intelligent control strategies for industrial automation. |
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| ISSN: | 2079-3197 |