Utilizing Raspberry-Pi 3 to Implement Fuzzy Logic Controller Optimized by Genetic Algorithm

The development of Fuzzy Logic Controllers (FLC) with low error rates and cost effectiveness has been the subject of numerous studies. This paper study goals to the investigation and then implementation an FLC using the readily accessible and reasonably priced Raspberry Pi technology. The FLC used i...

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Vydáno v:Iraqi journal for electrical and electronic engineering Ročník 21; číslo 2; s. 99 - 107
Hlavní autoři: Ibrahim Nasser, Amal, M. Kadhim, Hasan, Ahmed Hussien, Emad
Médium: Journal Article
Jazyk:angličtina
Vydáno: 15.12.2025
ISSN:1814-5892, 2078-6069
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Shrnutí:The development of Fuzzy Logic Controllers (FLC) with low error rates and cost effectiveness has been the subject of numerous studies. This paper study goals to the investigation and then implementation an FLC using the readily accessible and reasonably priced Raspberry Pi technology. The FLC used in this work has two inputs, one output, and five Membership Functions (MFs) for each input and output. The FLC goes through two processes, tweaking the MF parameters and tuning input/ output Scaling Factors. The tuning technique makes use of the Genetic Algorithm (GA). The whole set of the FLC probabilities is taken into account as the tuned FLC controller, and then transformed into a lookup table. The Center of Gravity (COG) approach is used to determine the output for the tuned FLC controller. The resulting table is converted into values of digital binary using a specific type of encoder, and then extraction of the set of Boolean functions to apply this tuned circuit. Finally, the Python 3 programming language is used to define the resultant Boolean functions on the Raspberry Pi platform, and then a decoder extracted the appropriate control action from the output. The Benefit of this method is the use of a digital numbering system to define the FLC, which is implemented on Raspberry Pi technology and allows for fuzzified high processing speed output per second. The controller speed has not been unaffected by the quantity for these fuzzy rules.
ISSN:1814-5892
2078-6069
DOI:10.37917/ijeee.21.2.10