A Fuzzy Proportional-Integral-Derivative Algorithm Based Control Method for Water Pump Motor in Waterworks

The study first analyzed the overall scheme of water pump motor control in the water plant, and then designed a fuzzy proportional-integral-derivative (PID) controller to control the water pump motor as needed. To improve control, the study introduces genetic algorithm to optimize the fuzzy rules and related parameters of PID controller. The results show that the adjustment time, steady-state error, and overshoot of the fuzzy PID controller based on genetic algorithm optimization are 0.12s, 0.01%, and 0.1%, respectively. This optimization scheme enables the controller to adjust the operating status of the water pump motor more flexibly and accurately when facing load fluctuations in the water supply system, ensuring stable output of water supply pressure and quantity. At the same time, this technology also provides reliable technical support for achieving intelligent and refined management of urban water supply.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/ic2ecs64405.2024.10928507
Primary Topic
Oil and Gas Production Techniques
Type
article
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article

A Fuzzy Proportional-Integral-Derivative Algorithm Based Control Method for Water Pump Motor in Waterworks

Tiantian Ma, Shixiang Chen, Guanghui Zhang, Xiaojun Xuan
Oil and Gas Production Techniques
article

A Fuzzy Proportional-Integral-Derivative Algorithm Based Control Method for Water Pump Motor in Waterworks

Tiantian Ma, Shixiang Chen, Guanghui Zhang, Xiaojun Xuan
article en

Abstract

The study first analyzed the overall scheme of water pump motor control in the water plant, and then designed a fuzzy proportional-integral-derivative (PID) controller to control the water pump motor as needed. To improve control, the study introduces genetic algorithm to optimize the fuzzy rules and related parameters of PID controller. The results show that the adjustment time, steady-state error, and overshoot of the fuzzy PID controller based on genetic algorithm optimization are 0.12s, 0.01%, and 0.1%, respectively. This optimization scheme enables the controller to adjust the operating status of the water pump motor more flexibly and accurately when facing load fluctuations in the water supply system, ensuring stable output of water supply pressure and quantity. At the same time, this technology also provides reliable technical support for achieving intelligent and refined management of urban water supply.

Hefei General Machinery Research Institute (China) (CN)
Clean water and sanitation
Openalex Percentile: Top 63%
Oil and Gas Production Techniques
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