Double Inverted Pendulum Model Implementation Using S-Functions

In this paper, we implemented a double inverted pendulum model using S-functions and conducted comprehensive simulation studies using state feedback control, optimal control, and fuzzy control approaches. The S-function implementation involved creating custom MATLAB/Simulink blocks that accurately represent the nonlinear dynamics of the double inverted pendulum system, including state-space formulations and real-time parameter adjustments. Through these simulations, we gained deep insights into the dynamic characteristics of the inverted pendulum system and explored how different control methodologies impact system behavior. The state feedback controller was designed using pole placement techniques, while the optimal controller employed LQR (Linear Quadratic Regulator) algorithms with properly tuned Q and R matrices. The fuzzy controller implementation utilized Mamdani-type fuzzy inference systems with carefully designed membership functions and rule bases. These research findings are significant for designing and optimizing inverted pendulum control systems and provide valuable references for further control algorithm development, particularly in handling complex nonlinear systems with multiple control strategies.