An adaptive self-adjusting fuzzy logic-based robust controller formulation for a class of uncertain MIMO nonlinear systems

This study presents a novel continuous controller, in conjunction with a fuzzy logic-based estimator, designed to address the compensation of parametric uncertainty in a category of high-order, multiple-input-multiple-output nonlinear systems. The proposed controller–estimator methodology tackles parametric uncertainties with self-adjusting adaptive fuzzy logic-based robust integral of sign of error algorithm. In the employed adaptive fuzzy logic (AFL) framework, the means and variances of the membership functions are updated online in each iteration, enabling a more accurate estimation of uncertainties. The boundedness of the closed-loop system and asymptotic stability of the error signals are verified via Lyapunov-based arguments. Numerical simulations are additionally presented to evaluate the efficacy of the proposed methodology.