Simple and Practical Fuzzy Control Algorithm Code Developed in MATLAB

This article presents a simple yet practical fuzzy control algorithm code developed in MATLAB. Fuzzy control algorithms represent a widely applied control methodology that mimics human reasoning patterns to handle complex nonlinear systems. The development of this code aims to make this algorithm more accessible and understandable, thereby contributing to technological advancement. During the coding process, we incorporated cutting-edge computer science techniques including deep learning and artificial intelligence to enhance the algorithm's accuracy and computational efficiency. The implementation utilizes MATLAB's Fuzzy Logic Toolbox for membership function definition, rule base creation, and defuzzification processes. Key functions include fuzzification of input variables, inference engine operations, and centroid-based defuzzification methods. Additionally, comprehensive documentation is provided with the code, featuring detailed explanations of parameter tuning, rule optimization techniques, and practical implementation examples. Through this code, users can gain deeper insights into fuzzy control principles and effectively apply them to solve real-world engineering problems.