Parafoil airdrop is an important way to deliver goods and materials to area where road vehicles are not easy to reach. However, it is difficult to deliver large quantities of goods and materials to a given location with only one parafoil. Airdropping multiple parafoils is an effective choice for transporting large quantities of goods and materials. To realize the cooperative airdrop of multiple parafoils, a cooperative guidance framework is proposed. First, a trajectory planning algorithm is designed to plan the multiphase trajectory for the parafoil group. Then, a trajectory tracking algorithm is developed for the pilot parafoil in the parafoil group to reliably follow the planned trajectory. Finally, a cooperative formation guidance strategy is designed based on the leader-follower consensus theory. Under this strategy, the position and speed of the follower parafoil can be consensus with those of the leader parafoil. Lyapunov's theorem proves the stability of this strategy. We evaluate the effectiveness of this framework through simulations. The results demonstrate that our algorithms can realize the precise airdrop of massive goods and materials with upwind landing using multiple parafoils. In addition, the parafoils could be gradually gathered to a desired formation, and safe distances could be maintained between parafoils during the airdrop process.

The airdropping of multi-parafoil systems is of great significance to earthquake relief and military material transportation. In order to achieve the coordinated motion of multiple parafoils, a formation guidance strategy based on a virtual structure is proposed, which enables the formation of multiple parafoils to follow the planned trajectory and land at the target precisely. Firstly, since the main movement mode of a parafoil is turning and gliding, a multiphase homing trajectory for the reference point is planned, which mainly consists of a turning and gliding phase. Then, the trajectories of all the points on the virtual structure are generated by superimposing the relative positions of the virtual structure on the planned trajectory. Based on Lyapunov stability theory, a guidance strategy is designed to guide all parafoils to track the corresponding points on the virtual structure and complete the desired formation task. The simulation results show that the guidance strategy based on a virtual structure can effectively guide multiple parafoils to achieve coordinated formation movement. Parafoils dropped from different positions and heading angles can gradually gather together and form a formation, track the planned trajectories, land at the target point precisely and align up against the wind.

The powered parafoil system is obtained by adding the propeller thrust to the unpowered parafoil system, and has coupling and nonlinear characteristics, which make its precise control more difficult than that of the unpowered parafoil system. To achieve the trajectory tracking control of the powered parafoil system in the field of precision airdrop, a mathematical model of the 6-DOF of the powered parafoil system is established first. Then, a new trajectory tracking strategy is proposed, which can overcome the limitations of the traditional guidance-based trajectory tracking strategy. We design lateral, longitudinal, and velocity controllers on the basis of the motion characteristics of the powered parafoil system. Then, we adopt the widely used PID control strategy in engineering. In response to the difficult of the PID controller parameter tuning of the powered parafoil system, we achieve the PID controller parameter tuning with the ecosystem particle swarm optimization (ESPSO) of the swarm intelligence optimization algorithm. The effectiveness of the algorithm is verified by simulation experiments. Results show that the proposed algorithm can obtain high trajectory tracking accuracy even when a deviation in the initial state and a random gust wind disturbance in the outside world occur regardless of the method of the multiphase homing or the optimal control homing adopted. The proposed trajectory tracking strategy also has strong robustness and adaptability.

Fixed-weight incremental model predictive control (IMPC) has been widely used for quadrotor trajectory tracking because of its predictive capability, but fixed performance weights limit adaptability to trajectory variations, model mismatch, and external disturbances. Existing adaptive MPC methods may require additional iterative parameter optimization or treat weight adaptation and disturbance suppression separately. To address these limitations, this paper proposes an adaptive-weight and disturbance-compensation IMPC (AWDC-IMPC). Unlike existing approaches, AWDC-IMPC coordinates an algebraic multi-factor weight-adjustment rule with residual-based lumped-disturbance compensation in a unified prediction framework. The weights are updated online according to trajectory curvature, position error, and acceleration-correction demand without additional iterative optimization. An LQR attitude controller completes the dual-loop architecture. Simulation comparisons show that AWDC-IMPC achieves lower tracking errors and smoother control than baseline IMPC and the evaluated benchmark controllers. Relative to IMPC, it reduces position-tracking RMSE by 75.72% without disturbances and 86.21% under the tested disturbances. Flight experiments confirm the feasibility and practical tracking performance of the controller, while 200 Monte Carlo trials provide evidence of robustness and performance consistency under bounded uncertainties. These results support the potential of AWDC-IMPC under the tested conditions; however, its performance in more diverse and challenging environments requires further investigation.

To address the problem of sudden failures during multi-parafoil formation transportation, a new fault formation reconstruction method based on the leader-following algorithm is proposed. First, monitoring of parafoil failures is established using an event-trigger mechanism within a numerical simulation framework. If a parafoil fails, the latest detachment time of a replacement parafoil is calculated based on its glide ratio to determine whether the altitude of the replacement parafoil meets the task reconstruction requirements. If it does, the formation is reconstructed using a switching control law for the replacement parafoil, enabling it to join the formation of the failed parafoil. Then, the leader-following algorithm is applied to reconstruct the formation, allowing the new multi-parafoil system to reorganize and complete the task in an orderly manner, with the replacement parafoil stably reaching the new target point as part of the reconstructed formation. Under this method, high-priority airdrop transportation tasks are ensured to be prioritized in the event of sudden failures during multi-parafoil formation operations. Lyapunov’s theory demonstrates the stability of this method. Simulation results validate the effectiveness of the framework, showing that the algorithm can successfully handle sudden failures of individual parafoils during multi-parafoil formation operations.

The obstacle avoidance flight of unmanned parafoil formations in complex terrains and under wind disturbances is essential for the success of airdrop missions. This study develops a comprehensive dynamic model of the parafoil and constructs a three-dimensional mountainous simulation environment. An obstacle avoidance algorithm based on the spatial velocity vector method is proposed, which dynamically regulates the parafoil’s motion through traction, avoidance, and guidance velocity vectors, thereby achieving efficient obstacle avoidance in complex wind fields. By incorporating a consensus-based leader-follower formation control strategy, the parafoil formation maintains both geometric configuration and heading stability during obstacle avoidance maneuvers. Simulation results demonstrate that the proposed method effectively enables safe obstacle avoidance and stable formation flight under wind disturbances, confirming the effectiveness of the algorithm.