In this article, we address the problem of robust fixed-time attitude stabilization for tilt trirotor unmanned aerial vehicle subjects to parameter uncertainties and external disturbances. First, a novel fixed-time stable system with a faster convergence rate is proposed. Second, a nonsingular fixed-time sliding mode surface is developed, which has better convergence performance than existing methods. Third, a continuous fast fixed-time sliding mode control law is proposed by applying the developed sliding mode surface and adaptive technique. As a result, the convergence time of the closed-loop system is bounded and independent of the initial conditions. Simulation and experiments are presented to verify that the proposed scheme can effectively and rapidly achieve attitude stabilization while maintaining high control precision and robustness.

In this article, a multilayered and distributed architecture for mission-oriented miniature fixed-wing UAV swarms is presented. Based on the concept of modularity, the proposed architecture divides the overall system into five layers: 1) low-level control layer; 2) high-level control layer; 3) coordination layer; 4) communication layer; and 5) human interaction layer, and many modules that can be viewed as black boxes with interfaces of inputs and outputs. In this way, not only the complexity of developing a large system can be reduced but also the versatility of supporting diversified missions can be ensured. Furthermore, the proposed architecture is fully distributed that each UAV performs the decision-making procedure autonomously so as to achieve better scalability. Moreover, different kinds of aerial platforms can be feasibly extended by using the control allocation matrices and the integrated hardware box. A prototype swarm system based on the proposed architecture is built and the proposed architecture is evaluated through field experiments with a scale of 21 fixed-wing UAVs. Particularly, to the best of our knowledge, this article is the first work which successfully demonstrates formation flight, target recognition, and tracking missions within an integrated architecture for fixed-wing UAV swarms through field experiments.

In this paper, a curved path following scheme with the aid of the vector field (VF) and the notion of input-to-state stable (ISS) for a fixed-wing unmanned aerial vehicle (UAV) is developed. The VF strategy is a robust and valid guidance method and its stability is proved using ISS properties. Many existing path following algorithms for fixed-wing UAVs are only proposed for straight-lines and orbits. However, the path required to be followed is always in approximate curves rather than straight-lines and orbits in many high-level missions, such as obstacle avoidance, search, and surveillance. The nonlinear-theoretic notion of ISS is playing a central role in the control law design and stability analysis. The error kinematics are converted into two interconnected subsystems with proven ISS properties, which yield the overall system that is globally asymptotically stable, i.e., and the along-track error and the cross-track error asymptotically approach zeros from any initial position in the space. The followed path is defined in terms of the arc-length parameter, and it can be expanded according to the waypoint fitting without the need to obtain a global function representation. The singularity of multiple closest points on the path is eliminated by constructing a speed profile of a virtual point on the path. The scheme is validated with a semi-physical experiment combined by an actual autopilot, ground station and the X-Plane flight simulator. Flight tests using a small fixed-wing UAV show excellent tracking performance of the curved path following.

This paper proposes a spatio-temporal trajectory tracking protocol for a fixed-wing unmanned aerial vehicle (UAV) subject to unknown disturbances and input saturation, using the exponential predefined time control (EPTC). Firstly, aiming at the problem that the control magnitude may grow violently while approaching the predefined time, we introduce an exponential controller to compensate for the predefined time controller. Then, fixed time disturbance observers (FTDOs) are designed to estimate the unknown external disturbances and unmodeled terms of the fixed-wing UAV. The nonlinear input saturation is linearized by a Gaussian error function (GEF) and addressed by auxiliary variables. Through rigorous analysis, we prove that FTDOs will converge within a fixed time and that tracking errors are bounded within this period. In the presence of input saturation, the tracking errors can converge to zero within a predefined time, irrespective of the initial states. The results of numerical simulations demonstrate that the proposed protocol can guarantee the convergence of the tracking errors within a predefined time. That is, the EPTC protocol has a spatio-temporal characterization. The change in the control magnitude is moderate compared to the existing works, which is more suitable for the fixed-wing UAV. Moreover, the flight test realizes the extension on a real fixed-wing UAV and verifies the practical feasibility of the proposed spatio-temporal trajectory tracking protocol.