Explore MATLAB source code curated for "模糊控制" with clean implementations, documentation, and examples.
A SIMULINK simulation was conducted to compare the control performance of a fuzzy self-tuning PID controller and a conventional PID controller applied to the same first-order inertial system, with MATLAB implementation details highlighting tuning methodologies and parameter adaptation algorithms.
A fuzzy control program implemented through MATLAB Simulink toolbox, designed for handling data processing under input uncertainty using rule-based inference mechanisms and membership functions.
This is my graduate-level Intelligent Computing course project featuring executable MATLAB m-files and Simulink mdl files implementing fuzzy control systems with complete algorithm implementations.
Implementation of fuzzy control and neural network control strategies for single inverted pendulum systems within Simulink simulation environments. Usage note: For fuzzy controller execution, first import the *.fis file into the MATLAB workspace using the readfis() function before running the simulation to ensure proper initialization of fuzzy inference systems.
A fuzzy control program developed using MATLAB Simulink toolbox, designed for effective data processing under input uncertainty conditions. Implementation includes fuzzy inference system configuration and rule-based decision making algorithms.
Simulation of double inverted pendulum system using Simulink for fuzzy control implementation with model design and parameter optimization
A practical fuzzy control algorithm for robot trajectory tracking with detailed implementation insights
This program demonstrates how to implement fuzzy control in MATLAB through custom development, without relying on MATLAB's built-in Fuzzy Logic Toolbox.
MATLAB-based simulation study of fuzzy adaptive PID controller addressing limitations of traditional PID controllers in automatic parameter adjustment when system dynamics change. This approach combines fuzzy logic with PID control to enable online self-tuning of PID parameters using fuzzy inference methods, resulting in improved controller adaptability. The MATLAB simulation demonstrates enhanced dynamic performance of the system through implementation of membership functions, rule bases, and defuzzification techniques.
This repository contains my MATLAB implementations for cart-inverted pendulum control systems using both classic PID and fuzzy control methods. It serves as an excellent resource for beginners learning fuzzy control, featuring detailed comparisons between traditional PID control and fuzzy logic approaches. The implementation includes controller design, simulation models, and performance analysis algorithms.