Optimizing Inverted Pendulum Stability: Performance Analysis of Self-Tuning Fuzzy PID and PID

The inverted pendulum system is a typical control problem for comparing advanced control approaches because of its unstable and nonlinear characteristics. Balancing the kind of system described is fundamental to many branches of engineering such as robotics, aeronautical systems, and automobile dynamics. In this work, the comparative ability of Self-Tuning Fuzzy PID and the traditional PID to stabilize an inverted pendulum system is investigated. The main issue resolved is the performance constraint of fixed-gain PID controllers in dynamic operating conditions. For this purpose, the Self-Tuning Fuzzy PID controller uses a fuzzy inference system to adaptively vary PID gains in real time, which supports better adaptability and disturbance rejection. In contrast, the traditional PID controller with fixed gain parameters renders suboptimal output when the operating conditions change. Simulations carried out in the Simulink platform compare the two control schemes in terms of stability parameters such as overshoot, settling time, rise time, and steady-state error. Outcomes show that the traditional PID controller has a rise time of 1.2s, an overshoot of 20%, and a settling time of 5s, resulting in slower stabilization and more oscillations. The Self-Tuning Fuzzy PID controller greatly enhances transient response, minimizing rise time to 0.8s, overshoot to 5%, and settling time to 2.5s, thereby stabilizing faster and with better robustness.