The control of Twin-Rotor Multi-Input Multi-Output (TRMS) systems presents a significant challenge due to high nonlinearity, strong aerodynamic cross-coupling, and the inevitable discrepancies between theoretical models and physical plants. This paper first exposes the instability of conventional Backstepping control under real hardware conditions, where unmodeled dynamics and parametric uncertainties drive the yaw subsystem into divergent oscillation, then proposes and experimentally validates two advanced architectures to overcome this limitation. The first is an online adaptive Backstepping gain-tuning scheme based on a novel Rate-Constrained Sequential Quantum Black Hole Optimization (RS-QBHO) algorithm. The second is a Hybrid Backstepping–Sliding Mode Control (BSMC) architecture that integrates structural disturbance rejection directly into the recursive design. Both schemes are formally verified via Lyapunov stability analysis and validated on a physical TRMS rig under identical hardware-in-the-loop conditions. Experimental results confirm that while the standard Backstepping controller failed in the yaw axis with an RMSE of 2.5624 rad, both proposed methods achieved stabilization. The QBHO-tuned controller yielded RMSE values of 0.0799 rad for pitch and 0.2305 rad for yaw, while the BSMC strategy proved superior, achieving 0.0682 rad and 0.1858 rad, respectively. These findings demonstrate that while meta-heuristic optimization effectively compensates for parametric mismatches, the passive disturbance rejection of the sliding mode term offers a more effective solution for mitigating unmodeled aerodynamic dynamics in MIMO flight platforms.
Kacimi et al. (2026) studied this question.