A fuzzy control algorithm for tracing air pollution based on unmanned aerial vehicles

The process of atmospheric pollutants traceability based on unmanned aerial vehicles (UAVs) is affected by many factors that can impact and increase the complexity of the traceability of atmospheric pollutants. In this study, we proposed a new algorithm called the fuzzy control traceability (FCT) to...

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Vydáno v:Journal of the Air & Waste Management Association (1995) Ročník 72; číslo 10; s. 1174 - 1190
Hlavní autoři: Jiang, Xinyan, Ding, Tao, He, Yuting, Cui, Xuelin, Liu, Zhenguo, Zhang, Zhenming
Médium: Journal Article
Jazyk:angličtina
Vydáno: Pittsburgh Taylor & Francis 03.10.2022
Taylor & Francis Ltd
Témata:
Air pollution
Algorithms
Control algorithms
Control systems design
Control theory
Controllers
Drones
Fuzzy control
Fuzzy logic
Odor
Plumes
Pollutants
Unmanned aerial vehicles
ISSN:1096-2247, 2162-2906, 2162-2906
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Shrnutí:The process of atmospheric pollutants traceability based on unmanned aerial vehicles (UAVs) is affected by many factors that can impact and increase the complexity of the traceability of atmospheric pollutants. In this study, we proposed a new algorithm called the fuzzy control traceability (FCT) to track odor plumes. Our proposed algorithm combined the characteristics and fuzzy control of the UAV and designed a controller based on the actual environment of the UAV. The fuzzy controller fuzzed the input gas concentration information, established fuzzy control rules by imitating human brain thinking, and outputted the turning angle and the move length according to rules, thus realizing intelligent tracking of the odor plume by the UAV. We compared the FCT algorithm with the bio-inspired "ZigZag" algorithm to validate its performance. Various concentration fields were constructed, and ten sets of experiments are performed using the two algorithms in different concentration fields. The average success rate of the FCT algorithm under different concentration fields was 95.4% higher than that of the ZigZag algorithm. Implications: Fuzzy control logic is applied to the field of air pollutant traceability of drones, and a single drone traceability algorithm based on fuzzy control is proposed; and in view of the shortcomings of a single traceability subject in the traceability, multiple traceability subjects are introduced to optimize fuzzy control.
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ISSN:1096-2247
2162-2906
2162-2906
DOI:10.1080/10962247.2022.2102093