SMART CONTROL WITH FUZZY LOGIC: A MULTI-APPLICATION FIS-BASED COMPARATIVE ANALYSIS
DOI:
https://doi.org/10.35631/IJIREV.825013Keywords:
Fuzzy Controller, Fuzzy Inference System, Fuzzy Logic, Mamdani Fuzzy Logic, Smart ControlAbstract
Fuzzy logic controllers (FLCs) have proven applicable in a wide range of smart control applications by handling imprecision, uncertainties and mimicking human reasoning. This paper presents a comparative study of FIS-based projects in diverse domains of smart controller which includes air-conditioning, washing machine, an irrigation system, and traffic-light. The system uses linguistic inputs and produces control outputs. All systems employ Mamdani-Fuzzy inference system type with triangular and trapezoidal membership functions. The rule bases on the order of 27 to 81 rules. This study summarizes each project based on inputs, outputs, membership functions, rule evaluation, and defuzzification method and the compare their performance in the term of responsiveness, service efficiency, and resource usage. Results indicate that fuzzy controllers can significantly improve efficiency and adaptively tuning control actions. The findings and analysis highlight the common design patterns of fuzzification process and its challenges for rule explosion involving many inputs. A generalized FIS framework and methodology framework was introduced to illustrate the collective architecture as a guideline in future endeavours. This synthesis not only demonstrates the versatility of fuzzy logic in automation and resource management but also serves as a reference survey of FIS design. The paper concludes with some limitations for further optimization in adaptive neural or Sugeno extensions and suggests best practices for implementing fuzzy controllers in design automation.
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