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Neuro-fuzzy controller based on adaptive neuro-fuzzy inference system (ANFIS) is proposed for swinging up a double pendulum from its hanging position to the inverted position. The controller is designed through two stages. In learning stage, the controller, which is an inverse mapping model from state variable to controlled quantity, is constructed off-line. While in control stage, control output is derived from the built model. To obtain training samples for inverse mapping model, hybrid genetic algorithms are applied to optimize computation of state variables and control law during the swing-up. Simulation results showed the effectiveness of the controller and the theoretical discussions.