In this article, a distributed control algorithm for a large-scale fixed-wing unmanned aerial vehicle (UAV) swarm system of collision avoidance and formation maneuver is proposed, which can meet the demands of a dense swarm with collaborative autonomy. First, a novel structure of a swarm is introduced, which can provide the reserved maneuverable space for UAVs during the flight. Besides, inspired by the movement of bird flocks, the light transmission model is proposed to improve the conventional potential field functions, which can realize the UAV swarm with the capability of repulsion in the short-range, speed and position cooperation in the middle range, and attraction in the remote range. Then, the distributed control architecture and the control algorithm of UAVs are designed, and the stability of the swarm is proved correspondingly. In the end, several numerical simulation results show the effectiveness and superiority of the proposed method, which illustrates the distributed control architecture of the swarm system to be more adaptable, stable, and scalable. Therefore, the proposed control algorithm provides strong theoretical support for the actual application in a large-scale fixed-wing UAV swarm system collaborative autonomy.

This paper proposes a novel prescribed-time cooperative guidance law (PTCGL) for multiple missiles cooperatively attacking a manoeuvring target. Guidance models in two directions are used and the acceleration saturations are also considered in both two directions. In line-of-sight (LOS) direction, by applying prescribed-time multi-agent consensus theory, the problem of the times-to-go ( $T_{gos}$) of multiple missiles converging to a same value is transformed into a stabilisation problem. Then the cooperative guidance law in LOS direction is designed based on the prescribed time integral sliding mode surface (PTISMS) and a new variable coefficient exponential reaching law, and a first-order auxiliary system is introduced to deal with the input saturation problem; based on a prescribed time linear sliding surface (PTLSMS), the cooperative guidance law in normal LOS direction is designed to ensure the LOS angle and LOS angle rate convergence within a prescribed time, and a second-order auxiliary system is designed to deal with the input saturation problem. Furthermore, the prescribed time convergence of the PTCGL is proved with the Lyapunov stability theory. Finally, numerical simulations demonstrate the effectiveness and advantages of the proposed PTCGL.

The maneuvering of a large-scale unmanned aerial vehicle (UAV) swarm, notable for flexible flight with collision-free, is still challenging due to the significant number of UAVs and the compact configuration of the swarm. In light of this problem, a novel parallel control method that utilizes space and time transformation is proposed. First, the swarm is decomposed based on a grouping-hierarchical strategy, while the distinct flight roles are assigned to each UAV. Then, to achieve the desired configuration (DCF) in the real world, a bijection transformation is conducted in the space domain, converting an arbitrarily general configuration (GCF) into a standard configuration (SCF) in the virtual space. Further, to improve the flexibility of the swarm, the time scaling transformation is adopted in the time domain, which ensures the desired prescribed-time convergence of the swarm independent of initial conditions. Finally, simulation results demonstrate that collision-free maneuvering, including formation changes and turning, can be effectively and rapidly achieved by the proposed parallel control method. Overall, this research contributes a viable solution for enhancing cooperation among large-scale UAV swarms.

In this paper, to address the cooperative localisation of a heterogeneous UAV swarm in the GNSS-denied environment, an adaptive simulated annealing-particle swarm optimisation (SA-PSO) cooperative localisation algorithm is proposed. Firstly, the forming principle of the communication and measurement framework is investigated in light of a heterogeneous UAV swarm composition. Secondly, a reasonably cooperative localisation function is established based on the proposed forming principle, which can minimise the relative localisation error with limited available information. Then, an adaptive weight principle is incorporated into the particle swarm optimisation (PSO) for better performance. Furthermore, in order to overcome the drawbacks of PSO algorithm easily falling into the local extreme point, an adaptive SA-PSO algorithm is improved to promote the convergence speed of cooperative localisation. Finally, comparative simulations are performed among the adaptive SA-PSO, adaptive PSO, and PSO algorithms to demonstrate the feasibility and superiority of the proposed adaptive SA-PSO algorithm. Simulation results show that the proposed algorithm has better performance in convergence speed, and the cooperative localisation precision can be guaranteed.

In order to overcome the drawbacks of the convergence time boundary dependent on tuning parameters in existing finite/fixed-time cooperative guidance law, this paper presents a three-dimensional prescribed-time pinning group cooperative guidance scheme that ensures multiple unpowered missiles to intercept multiple stationary targets. Firstly, combining a prescribed-time scaling function with pinning group consensus theory, the prescribed-time consensus-based cooperative guidance law is proposed. Secondly, the prescribed-time convergence of the proposed pinning group consensus-based cooperative guidance law proves that the convergence can be achieved at a specified time, regardless of initial conditions and parameters. Furthermore, the design steps including two stages of the proposed guidance law are given for engineering application. Extensive simulations are carried out in three cases to verify the properties. Simulation results show the effectiveness and superiority of the proposed prescribed-time consensus-based cooperative guidance scheme.