This paper presents the development of an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller for a mid-pivot Ball and Beam system. The nonlinear dynamic model is derived using Euler–Lagrange formulation, followed by DC motor modeling to construct the full state-space system. An ANFIS controller is trained from PID-generated data to enhance adaptability under nonlinear conditions. Simulation and hardware experiments validate the controller’s performance. Results show that the proposed controller can stabilize the system with reasonable accuracy, although overshoot and oscillation remain. Directions for improving intelligent control and hardware design are discussed.
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