This study proposes a robust cascaded hybrid control architecture combining the Linear Quadratic Regulator (LQR) with Super-Twisting Sliding Mode Control (STSMC) to address the attitude stabilization problem of underactuated quadrotor UAVs. In this framework, the inner LQR loop ensures optimal stabilization, while the outer STSMC loops provide robust reference modification to compensate for uncertainties. To maximize the robustness of the proposed hybrid architecture, the parameters of the STSMC component were globally optimized using the Big Bang-Big Crunch (BB-BC) algorithm. The effectiveness of the proposed strategy is rigorously evaluated on the Quanser 3-DOF Hover system model against two distinct benchmarks: the classical LQR and the optimization-based Model Predictive Control (MPC). Comprehensive simulation scenarios were conducted, including stochastic wind disturbances, time varying thrust coefficients, sudden payload release, and critical motor failure. Additionally, a virtual 3D spatial analysis based on kinematic reconstruction was performed to validate the positional stability of the rotor tips. The comparative results demonstrate that while the MPC controller exhibits a faster transient response compared to the classical LQR, it suffers from significant performance degradation under model mismatches. In contrast, the proposed LQR-STSMC consistently outperforms both benchmarks, achieving error metrics (ISE, IAE, and ITAE) orders of magnitude lower than the competitors. The findings confirm that the hybrid scheme offers superior fault tolerance, faster stabilization, and precise tracking capabilities, making it a highly reliable alternative for safety critical flight operations in uncertain environments.
Budak et al. (Wed,) studied this question.