Fractional-Order Reference Model-Based Adaptive Feedback Linearization for Delta Manipulator

This paper presents a novel Fractional-Order Model Reference Adaptive Control (FO-MRAC) strategy for the adaptive feedback linearization of a nonlinear Delta parallel robot. By leveraging fractional calculus, the proposed approach enhances both robustness and adaptability in the presence of model uncertainties. The fractional-order framework enables a more accurate representation of the robot’s dynamics by capturing memory effects and viscoelastic behavior phenomena typically neglected in integer-order models. The adaptive control mechanism continuously adjusts the controller parameters in real time, ensuring precise trajectory tracking without requiring exact knowledge of the system model.