Fuzzy Algorithm-Based PID Control for First-Order Inverted Pendulum

This project implements PID control for a first-order inverted pendulum using a fuzzy algorithm, achieved through the T-S model approach in fuzzy control. The inverted pendulum represents a classic control engineering problem frequently used to study and test the performance of various control algorithms. In this implementation, we employ a fuzzy control algorithm to enhance the control effectiveness of the inverted pendulum system. Fuzzy control is a methodology based on fuzzy logic that effectively handles uncertainty and ambiguity, making it suitable for diverse complex control systems. The T-S (Takagi-Sugeno) model, a widely-used fuzzy control framework, divides the system into multiple local regions and applies fuzzy rules for control within each region. From a code implementation perspective, the system typically involves defining membership functions for pendulum angle and angular velocity, establishing fuzzy rule bases using if-then statements, and calculating precise control outputs through defuzzification processes. The PID parameters are dynamically adjusted based on the fuzzy inference system's output, where the fuzzy controller evaluates system states and determines appropriate PID gain adjustments. By implementing fuzzy algorithm-based PID control for the first-order inverted pendulum, we gain deeper insights into the practical application of fuzzy control in real-world control problems and demonstrate how fuzzy logic can optimize traditional PID controller performance under nonlinear conditions.