In this article, we propose a solution to the problem of path following for a quadcopter aircraft with unknown vehicle parameters (mass and moment of inertia) and external disturbances. By employing the backstepping technique, the proposed adaptive control strategy guarantees the following: the quadcopter is globally steered toward, and kept within, an arbitrarily small neighborhood of a desired smooth path, achieving global uniformly ultimately boundedness; compared to trajectory tracking, a smoother convergence is obtained as the control actuation signals (thrust force and torque) are bounded with respect to the position error, and the designed timing law ensures that the desired path starts to move only when the vehicle gets close to the desired path; and a single adaptive control law can be used for accurate motion control of aerial vehicles with a wide range of inertial properties, without the need for retuning control gains or other parameters. Moreover, the controller is also made robust to external constant and slowly time-varying disturbances through the design of disturbance estimators. To demonstrate the effectiveness and performance of the proposed control strategies, simulation and experimental results are presented and analyzed.

This article investigates the attitude control problem for a novel foldable wave-energy powered autonomous underwater vehicle (FWEPAUV) with model uncertainties and external disturbances. To find a trade-off between the control accuracy and control energy consumption, a robust performance-prescribed optimized backstepping control (RPOBC) scheme is designed for optimal tracking problem by combining the reinforcement learning (RL) technique. The performance-prescribed mechanism is devised to ensure the prescribed tracking accuracy. To make the controller robust against the model uncertainties and external disturbances, an auxiliary system with a novel cost function is introduced into the optimized backstepping (OB) framework. Besides, the theoretical analysis indicates that the RPOBC scheme can guarantee tracking errors converge to predefined performance with an optimal control performance. At last, the simulation results are presented and analyzed to demonstrate the effectiveness of the designed RPOBC strategy.

In this paper, we address the tasks of trajectory tracking (TT) and path following (PF) for a hovercraft vehicle in the presence of uncertain parameters and unknown external disturbances. Building on the backstepping technique, the proposed TT (PF) control laws are able to drive a hovercraft toward and stay within a neighborhood of a reference trajectory (path), achieving global practical stability. Moreover, the devised control strategies also guarantee that the actuations remain bounded with respect to the position error. The controller is made robust to constant external disturbances and uncertain model parameters by the introduction of dynamic estimators for the disturbance and friction coefficients. A projection operator is used to ensure the estimates remain within prescribed bounds and are sufficiently smooth to be backstepped. In order to validate the efficacy and performance of the proposed controllers, we present and analyze both simulation and experimental results.

This article focuses on the issue of adaptive multi-event-triggered fuzzy dynamic positioning control of unmanned surface vehicles against denial-of-service attacks within a finite-time interval. To improve the data transmission efficiency, an innovative adaptive multi-event-triggered mechanism is designed to dynamically adjust the event-triggered thresholds. Especially, the asynchrony between the membership functions of the controller and that of the system is embedded into the adaptive multi-event-triggered mechanism, which can help to reduce the conservatism of controller design attributed to mismatched membership functions. By employing the linear matrix inequality technology, sufficient conditions are derived to ensure that the switched closed-loop fuzzy dynamic positioning system is finite-time bounded with an ${\mathcal {H}}_{\infty }$ noise attenuation performance. To clarify the validity of the presented positioning controller under the adaptive multi-event-triggered mechanism and denial-of-service attacks, we provide and analyze the simulation results.