Design and Experimental Attitude Control of Quadrotor Via Optimized Adaptive IT-2 FLC Integrated with Nonlinear FOPID

This paper presents an adaptive Interval Type-2 Fuzzy Logic Controller (IT2-FLC) integrated with a nonlinear Fractional-Order Proportional Integral-Derivative (FOPID) controller for quadrotor attitude control. The adaptive mechanism, based on sliding surfaces, tunes the controller parameters in real-time. Moreover, the fuzzy system is integrated with a nonlinear FOPID controller. Unlike the fixed gains of the conventional FOPID, the nonlinear variant dynamically adjusts its parameters in real-time. The Grey Wolf Optimizer (GWO) is used to optimize both controller and fuzzy system parameters, minimizing the Integral of the Absolute Error (IAE). To validate the effectiveness of the proposed controller, three configurations — IT2-FLC integrated with FOPID, adaptive IT2-FLC integrated with FOPID and IT2-FLC integrated with nonlinear FOPID — are designed for the attitude control of a quadrotor, all aiming to achieve the same objective function. The results show that nonlinear gain alone improves performance more than the adaptive structure alone in all axes. For the roll axis, nonlinear gain reduces IAE and RMSE by 55.08% and 40.80%, respectively, while the adaptive structure achieves smaller improvements of 34.62% and 17.24%. In the pitch axis, nonlinear gain reduces IAE and RMSE by 37.36% and 18.10%, compared to 30.27% and 8.45% with the adaptive structure. Combining nonlinear gain with the adaptive structure leads to the best performance in all cases, with the largest improvements in IAE, MAE and RMSE observed in the roll and yaw axes.