*Result*: Utilizing Raspberry-Pi 3 to Implement Fuzzy Logic Controller Optimized by Genetic Algorithm.
*Further Information*
*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. [ABSTRACT FROM AUTHOR]*
*تركز هذه المقالة على تصميم وتنفيذ متحكم منطقي ضبابي (FLC) محسن بواسطة خوارزمية جينية (GA) باستخدام منصة راسبيري باي 3. تطور الدراسة متحكمًا منطقيًا ضبابيًا يحتوي على مدخلين ومخرج واحد، لكل منها خمس دوال انتماء، وتطبق الخوارزمية الجينية لتحسين عوامل مقياس المدخلات/المخرجات ومعلمات دوال الانتماء بهدف تقليل التكامل التربيعي للخطأ (ISE) في نظام تحكم مغلق الحلقة. يتم ترميز المتحكم الضبابي المحسن إلى دوال بوليانية وتنفيذه على راسبيري باي 3 باستخدام لغة بايثون، مما يتيح معالجة رقمية عالية السرعة مستقلة عن عدد قواعد المنطق الضبابي. توضح الأبحاث أن دمج المنطق الضبابي مع الخوارزميات الجينية يعزز أداء المتحكم بشكل فعال، بينما يوفر راسبيري باي 3 منصة أجهزة منخفضة التكلفة ومناسبة لمثل هذه التطبيقات. [Extracted from the article]
Copyright of Iraqi Journal for Electrical & Electronic Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)*