This study introduces an innovative control strategy utilizing a nonsingular fast sliding mode technique tailored for robotic systems. The core of this approach lies in the development of a type-2 fuzzy logic-based nominal model, meticulously designed to accurately approximate the dynamics of the real system while adeptly handling the variability in system parameters. This method marks a departure from conventional approaches by inferring the switch signal for type-2 adaptive fuzzy systems, a critical step in achieving superior tracking performance without the necessity for extensive knowledge of the system's upper bounds in uncertainties and external disturbances. The efficacy of the proposed control law is rigorously validated through a series of simulations, encompassing a variety of initial conditions and reference signals, thereby demonstrating its robust performance capabilities.
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