Rosales Claudio, Vacca Sisterna Carlos, Rossomando Francisco, Gandolfo Daniel, Soria Carlos, Carelli Ricardo
Automatic Institute (INAUT), National University of San Juan, CONICET. Avda. Libertador San Martín (Oeste) 1109, CP 5400, San Juan, Argentina.
ISA Trans. 2025 Nov;166:241-249. doi: 10.1016/j.isatra.2025.07.029. Epub 2025 Jul 23.
This paper proposes a novel methodology for the design of robust and adaptive controllers tailored to unmanned aerial vehicles (UAVs). The proposed control architecture integrates a Super-Twisting Sliding Mode Controller (ST-SMC) with an adaptive law to ensure high-performance trajectory tracking under model uncertainties and external disturbances. The ST-SMC effectively mitigates the chattering phenomenon, a common issue in sliding mode control schemes, while maintaining robustness to system nonlinearities. The adaptive component dynamically updates the control parameters in real time to compensate for unmodeled dynamics and parameter variations. The combined approach synergistically improves tracking accuracy and overall system stability. A rigorous stability analysis based on Lyapunov theory guarantees the convergence and boundedness of the control errors. The effectiveness of the proposed method is validated through experimental laboratory flights in a sensor-enhanced environment. The results demonstrate that the two control schemes complement each other, achieving a robust strategy with high performance in the presence of parametric uncertainties.
本文提出了一种新颖的方法,用于设计适用于无人机(UAV)的鲁棒自适应控制器。所提出的控制架构将超扭曲滑模控制器(ST-SMC)与自适应律相结合,以确保在模型不确定性和外部干扰下实现高性能轨迹跟踪。ST-SMC有效减轻了滑模控制方案中常见的抖振现象,同时保持对系统非线性的鲁棒性。自适应组件实时动态更新控制参数,以补偿未建模动态和参数变化。这种组合方法协同提高了跟踪精度和整体系统稳定性。基于李雅普诺夫理论的严格稳定性分析保证了控制误差的收敛性和有界性。所提方法的有效性通过在传感器增强环境中的实验室内飞行得到验证。结果表明,这两种控制方案相互补充,在存在参数不确定性的情况下实现了高性能的鲁棒策略。