This paper addresses the consensus control challenge in 6-degree-of-freedom (6-DOF) fixed-wing multi-unmanned aerial vehicle (multi-UAV) systems with switching topologies. The primary obstacle in achieving this goal stems from handling asynchronous topology switching induced by topology identification delays during cooperative flight. Effectively mitigating these issues involves implementing an asynchronous switched observer design that incorporates the intrinsic mechanisms of switching topologies and a topology switching law design. In contrast to current state-of-the-art approaches, we introduce a novel piecewise Lyapunov function. Not only does it align with the asynchronous switching characteristic, where the system employs the same controller/observer during the matching interval of the previous topology mode and the non-matching interval of the current topology mode, but it also yields a more lenient topology switching law. This is ensured by guaranteeing that the Lyapunov function continues to decrease in the non-matching interval. Subsequently, we design an adaptive fuzzy fault-tolerant translational/rotational controller, ensuring a minimal consensus tracking error. Comparative simulations are conducted to underscore the superiorities of the proposed strategy.

A coordinated control challenge is addressed in 6-degree-of-freedom (6-DOF) fixed-wing multiple unmanned aerial vehicle (multi-UAV) systems under communication and state constraints. The primary obstacle in achieving this goal arises from managing frequent information interactions and the assurance that UAV states converge within prescribed bounds. On the one hand, a novel dynamic self-triggering mechanism is effectively proposed. Unlike current state-of-the-art approaches, the proposed dynamic self-triggering communication mechanism features a larger triggering threshold and eliminates the need for continuous monitoring of system state information. This reduces the demand on system communication and sensor resources. On the other hand, a new time-varying constraint bounded function is introduced to effectively relax restrictions on the initial system state. Then, the coordinated translational/rotational controllers are designed to ensure minimal consensus tracking error. Semi-physical simulations highlight the effectiveness of the proposed control algorithm.

The event-triggered synchronization problem for six-degree-of-freedom fixed-wing multiple unmanned aerial vehicles (UAVs) over a directed spanning tree topology is addressed in this work. The primary challenges lie in handling intermittent neighboring state information caused by event-triggered communication. To address this limitation, a smooth auxiliary function is designed to ensure a smooth transition to the triggered value within each triggering interval by updating the maximum state rate. The first-order distributed estimator incorporating the smooth function is directly applied to the backstepping framework for rotational dynamics, guaranteeing the differentiability of the virtual control law. Compared to state-of-the-art methods, the proposed estimator features a lower order and exhibits stronger adaptability to track leader UAV's speed and attitude angles that are either aperiodic or non-zero constant. Additionally, a sign-independent compensation mechanism enhances control accuracy. The proposed method is validated through semi-physical simulation.

The cooperative flight of manned and unmanned aerial vehicles (MAV/UAVs) has recently become a focus in the research of civilian and humanitarian fields, in which formation control is crucial. This paper takes the improvement of convergence performance and resource conservation as the entry point to study control problems of cooperative formation configuration of MAV/UAVs. Following the backstepping recursive design procedures, an event-triggered fixed-time formation control strategy for MAV/UAVs operating under modeling uncertainties and external disturbances is presented. Moreover, a novel switching threshold event-triggered mechanism is introduced, which dynamically adjusts control signal updates based on system states. Compared with periodic sampling control (Controller 1), fixed threshold strategies (Controller 2) and relative threshold strategies (Controller 3), this mechanism enhances resource efficiency and prevents Zeno behavior. On the basis of Lyapunov stability theory, the closed-loop system is shown to be stable in the sense of the fixed-time concept. Numerical simulations are carried out in Simulink to validate the effectiveness of the theoretical findings. The results show that compared with the three comparison methods, the proposed control method saves 86%, 34%, and 43% of control transmission burden respectively, which significantly reduces the number of triggered events.