This paper investigates the collaborative defense problem of multiple unmanned aerial vehicles (UAVs) in a three-dimensional space with an important area. A two-phase defense strategy is proposed for multiple defending UAVs (defenders) to cooperatively prevent the adversarial UAVs (intruders) from approaching the important area. In the first phase, considering that a single defender may lack the ability to neutralize an intruder independently, a game-theoretical based coalition formation algorithm is proposed to drive defenders to form different-sized defending coalitions to neutralize multiple intruders with different abilities. In the second phase, once a defending coalition is established, a distributed enclosing control protocol is presented to guide the coalition members to collaboratively form an enclosing configuration around the detected intruder, the purpose of which is to restrict the movement of the intruder. Both the coalition formation algorithm and the enclosing control protocol are designed based on the local interactions with the neighboring defenders, which are scalable and executable. Simulation tests demonstrate the effectiveness of the proposed strategy. Meanwhile, the scalability and flexibility of the proposed strategy are also discussed in detail.

The consensus control problem under a leader-follower formation scenario is investigated in this paper, where the interactive link is considered as directed topology. A fixed-time distributed observer (FDO) is proposed to estimate the states of the leader node, whose states are supposed to be accessible for only partial followers. Furthermore, a weighted consensus protocol (WCP) is deployed on unmanned aerial vehicles (UAV) to attain formation tracking. The fixed-time convergence of FDO is proved through Lyapunov theories. A comparative simulation is conducted with FDO against a typical linear observer and WCP against a conventional consensus protocol. The results depict that the faster convergence speed and lower formation tracking error can be reached by FDO and WCP. An outdoor experiment with an unmanned ground vehicle (UGV) as leader and three quadrotor UAVs as followers is performed to enhance the application of the proposed approach.

This article proposes an integrated framework for unmanned aerial vehicles (UAVs) cooperative control, combining advanced distributed control strategies with human–swarm interaction mechanisms to address obstacle avoidance scenarios. First, distributed controllers are designed to explicitly account for observer errors. Specifically, first-order and high-order control barrier functions (CBFs), integrated with the bounded-error observer, are proposed and theoretically validated. These CBFs impose constraints on the control inputs to guarantee system safety during the entire operation. Second, a three-tier human–UAV swarm interaction architecture is introduced, enabling comprehensive human intervention across different operational levels. To verify the effectiveness and practicality of the proposed method, simulation experiments are conducted in a target tracking and rescue scenario. The integrated observer–controller design demonstrates superior performance over conventional approaches, exhibiting enhanced obstacle avoidance capabilities and robust disturbance rejection. The three-tier framework can effectively coordinate human–UAV swarm interaction and improve the efficiency of the swarm mission.

This paper utilizes the distributed model predictive control (DMPC) method to investigate the formation control problem of unmanned aerial vehicles (UAVs) in the obstacle environment and establishes cooperative capability evaluation metrics of the swarm. Based on the DMPC approach, the formation cost function is constructed to adjust the relative positions and velocities of UAVs, ensuring the desired formation. Additionally, to address the obstacle avoidance problem in the formation, the obstacle avoidance function is designed to provide safe formation control in the obstacle environment. To evaluate the cooperative capability of UAVs, we design evaluation metrics from multiple dimensions to reflect the swarm’s cooperative capability. Finally, the simulation results show the effectiveness of the formation control method with obstacle avoidance and the applicability of the swarm’s cooperative capability evaluation metrics.

This paper investigates the event-triggered consensus for a group of unmanned aerial vehicles (UAVs) with communication faults under the assumption that the position sensors of some individuals are damaged. The objective is to make the UAV group reach consensus in urgent tasks such as obstacle avoidance or evasion. Using the Lyapunov stability theory, sufficient conditions to achieve system consensus are given based on different velocity and position interaction topologies. Considering the limited capabilities of sensors and processors, an event-triggered consensus protocol is adopted to reduce the sampling frequency. Finally, simulation results illustrate the effectiveness of our approach.