MATLAB-based Fuzzy Control Model for Vehicle Parking System

The MATLAB-based fuzzy control model for vehicle parking represents an intelligent parking system capable of safely and reliably positioning vehicles within designated parking spaces. This model is designed using MATLAB's Fuzzy Logic Toolbox, which implements fuzzy logic processing for various parking phases to enhance system intelligence. The implementation typically involves defining input variables (such as distance to parking space, vehicle orientation, and speed) and output variables (steering angle and velocity) through MATLAB's fis (Fuzzy Inference System) structure. Key algorithmic considerations include not only the dimensions and shape of the parking space but also vehicle size, steering angles, and velocity parameters to ensure secure parking in confined areas. The model employs membership functions and rule-based reasoning to handle uncertainties in real-world parking scenarios. Developers can utilize MATLAB's rule editor to define conditional statements like "IF distance is close AND angle is large THEN steer sharply" to create comprehensive parking strategies. Furthermore, the model supports optimization adjustments based on user requirements through parameter tuning in MATLAB's fuzzy logic designer interface. This allows customization for different vehicle types and parking configurations. The system demonstrates high efficiency through MATLAB's simulation capabilities, where developers can test parking scenarios using Simulink integration and visualize performance metrics. In summary, this MATLAB-based fuzzy control model provides an efficient, intelligent, and secure parking solution that significantly enhances convenience in daily transportation. The code implementation leverages MATLAB's built-in functions like addvar, addmf, and addrule to construct the fuzzy logic controller, while plotfis and evalfis functions enable system analysis and validation.