Trajectory Tracking and Adaptive Disturbance Stability Control for a Coaxial Rotor AAV

Abstract

Rotary-wing configuration of autonomous aerial vehicles (AAVs) offers great flight efficiency for civil and military deployments. However, the control and trajectory tracking of certain AAVs, specifically coaxial rotor AAVs (CRAAVs) pose notable research challenges due to their under-actuated characteristics. To handle system dynamics and disturbance susceptibility problems, this research proposes a sophisticated control scheme for a CRAAV integrating a linear extended state observer (LESO) and the model reference adaptive control with an integrator (MRACI). Firstly, a dynamic model of the CRAAV based on Euler-Newton formalization is designed. Following this, a LESO technique is implemented to enhance robustness in estimating external disturbances and noises. Subsequently, the MRACI framework is developed, ensuring robust attitude and altitude tracking performance while alleviating control chattering. Furthermore, the closed-loop stability of the suggested LESO-MRACI controller is theoretically justified by the bounded LESO estimation error and Lyapunov-based convergence of the nominal tracking system. Finally, the research endeavors to present the proof-of-concept of the designed CRAAV system through simulation, lab-experiment, and real-time flight test. Findings of different evaluations reveal its outperformance in terms of tracking accuracy improvement along with less overshoot and steady-state errors and more stable control under external disturbances. The outcomes ensure the efficacy, robustness, and feasibility of the proposed aerodynamics configuration and controller. This research reflects significant contributions to facilitating the state-of-the-art in the evolving AAV domain and promoting real-world applications. Note to Practitioners—This paper overcomes the trajectory tracking and stability issues of a CRAAV deployed in environment under parametric and external disturbances. Our proposed solution integrates the LESO technique with MRACI scheme that enhances adaptability, tracking accuracy, and stability of the CRAAV. The designed framework is valuable for outdoor deployment, specifically for critical tasks, including search and rescue, surveillance, and delivery operations, leveraging AAV applications in full disturbed environments. The potential usage of this promising technology is beyond the conducted scenarios and experiments. Industries like emergency response and urban logistics that operate in dynamic, complex environments may benefit with the designed system. This would refine operational performance together with response time and safety.