In this paper, we focus on the transition control of a ducted fan vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV). To achieve a steady transition from hover to high-speed flight, a neural-networks-based controller is proposed to learn the system dynamics and compensate for the tracking error between the aircraft dynamics and the desired dynamic performance. In prior, we derive the nonlinear system model of the aircraft full-envelope dynamics. Then, we propose a novel neural-networks-based control scheme and apply it on the underactuated aircraft system. Key features of the proposed controller consist of projection operator, state predictor and dynamic-formed adaptive input. It is proved and guaranteed that the tracking errors of both state predictor and neural-networks weights are upper bounded during the whole neural-networks learning procedure. The very adaptive input is formed into a dynamic structure that helps achieve a reliable fast convergence performance of the proposed controller, especially in high-frequency disturbance conditions. Consequently, the closed-loop system of the aircraft is able to track a certain trajectory with desired dynamic performance. Satisfactory results are obtained from both simulations and practical flight test in accomplishing the designed flight course.

This paper presents a novel fixed time sliding mode disturbance observer (FTSMDO) based second-order fixed time sliding mode control (FTSMC) for small scale unmanned helicopter to do hover operations in the presence of external disturbances. Sliding mode control is insensitive to matched uncertainties but sensitive to mismatched uncertainties. The novel FTSMDO exactly estimates the total mismatched uncertainties effecting the sliding mode control performance. To counter the mismatched uncertainties a new sliding surface augmented by the total mismatched disturbance approximated by the FTSMDO is defined. The second-order FTSMC forces the system states to reach the sliding surface in fixed time and then on the sliding surface the system states exponentially converge to the desired equilibrium point. The control performance is compared with the disturbance observer based sliding mode controller (DOB-SMC) and shows superior performance.

This paper proposes a model predictive control (MPC) approach for ducted fan aerial robots using physics-informed machine learning (ML), where the task is to fully exploit the capabilities of the predictive control design with an accurate dynamic model by means of a hybrid modeling technique. For this purpose, an indigenously developed ducted fan miniature aerial vehicle with adequate flying capabilities is used. The physics-informed dynamical model is derived offline by considering the forces and moments acting on the platform. On the basis of the physics-informed model, a data-driven ML approach called adaptive sparse identification of nonlinear dynamics is utilized for model identification, estimation, and correction online. Thereafter, an MPC-based optimization problem is computed by updating the physics-informed states with the physics-informed ML model at each step, yielding an effective control performance. Closed-loop stability and recursive feasibility are ensured under sufficient conditions. Finally, a simulation study is conducted to concisely corroborate the efficacy of the presented framework.

For agile fixed-wing aerial robots, the vertical/horizontal flight mode transition is a fundamental requirement for high maneuverability. This letter focuses on a challenging implementation in which the aircraft conducts the transitional flight at fixed altitude along a straight path. Implemented on a small ducted fan fixed-wing, we propose a transition-corridor-based control strategy to conduct the flight transition neatly. The transition corridor is described as a region comprising all the admissible flight velocities, accelerations and attitudes, bounded by the capacity of both the propulsion and control system of the vehicle. By planning the transition trajectory in obedience with the identified transition corridor, as well as adopting a unified full envelope flight control scheme, the ducted fan fixed-wing successfully accomplishes the practical transitional flight. Experimental results are satisfactory in both flight mode transition and altitude stabilization.