This paper presents the design, optimization and implementation of a fuzzy controller applied to a rotatory inverted pendulum system, where a genetic algorithm is used to tune the parameters of the controller membership functions from experimental data. The proposed fuzzy control is based on a cascade control structure, which is useful for this nonlinear pendulum system. Furthermore, the LQR controller, which is commonly used to control an inverted pendulum system, was implemented for comparison purposes. It is empirically demonstrated that the proposed fuzzy controller covers a larger range of operating points than a conventional LQR controller. Finally, typical disturbances are added to the system states to test the robustness of the proposed fuzzy controller.