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.

To address two key issues in powered parafoil modeling and parameter identification, namely, the insufficient consideration of brake-induced additional drag in conventional six-degree-of-freedom powered parafoil models under high-maneuver flight conditions and the susceptibility of parameter identification to local optima, this paper proposes a six-degree-of-freedom dynamic modeling method incorporating explicit brake-induced drag correction and a prescribed propulsion-thrust input, together with an improved genetic algorithm–sequential quadratic programming (GA-SQP) hybrid parameter identification method. An additional drag term associated with symmetric brake deflection is introduced into the aerodynamic model, and the effects of differential brake deflection on the lateral-directional control moments are retained, thereby enhancing the model’s capability to describe continuous spiral and large-turning maneuvers. For the identification of 17 parameters, including aerodynamic derivatives, control-delay parameters, and wind-field compensation coefficients, ahybrid optimization framework integrating an adaptive genetic algorithm with sequential quadratic programming is developed. Flight-test validation shows that the improved GA-SQP method achieves a three-axis linear velocity root mean square error of 0.82 m/s, a horizontal-position root mean square error of 8.9 m, and a normalized attitude error of approximately 5.2%, outperforming the PSO, SA, an PS algorithms. The generalization capability of the identified model is evaluated using an independent field-flight dataset and further assessed on the RflySim platform. The results demonstrate that the identified parameters exhibit good predictive capability and environmental adaptability.

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.

Aiming at improving the mapping accuracy and autonomous navigation efficiency of rescue robot in unknown environment, an improved Hector SLAM based autonomous navigation strategy is proposed, which is implemented on the Levenberg-Marquardt optimization and Bezier smooth dynamic weighted $\text{A}^{\ast} $ algorithm. Firstly, the scan match process of Hector SLAM is performed by an improved Levenberg-Marquart (LM) method to solve the problems of non-convergence of functions and inaccurate local approximation caused by the non-singularity for solving the Hessian matrix. Secondly, the Bezier smooth dynamic weighted $\text{A}^{\ast} $ algorithm is utilized to perform autonomous navigation based on the SLAM map. In which, the navigation target points selection is employed by the frontier exploration strategy in order to solve the search efficiency as for the increasing number of nodes in the $\text{A}^{\ast} $ algorithm, and the accuracy of SLAM mapping declines owing to the large angle amplitude. Finally, the experiments are carried out in ROS, the results show that there is a better performance for proposed method to implement the high mapping accuracy and efficient autonomous navigation.

传统翼伞系统的航迹规划主要考虑落点精度及逆风着陆等指标,而当空投区域环境较为复杂,在翼伞系统归航路径上存在障碍时,如何规避这些障碍也成为翼伞系统航迹规划所必须要考虑的因素.针对翼伞空投过程有可能遇到高山或者高大建筑物阻碍的问题,提出了一种复杂环境下翼伞系统的组合式航迹规划策略.该方法将翼伞空投的区域分为障碍区和着陆区,在障碍区中采用快速搜索随机树(RRT)算法进行可行路径搜索,考虑到RRT算法生成的轨迹包含棱角,导致路径不够平滑的问题,结合翼伞系统质点模型的运动特性,对其进行了适用性改进,以使规划的航迹满足实际翼伞空投需求.为了解决RRT算法搜索方向随机,难以满足逆风着陆的问题,当翼伞系统进入着陆区后采用分段归航的方式设计航迹,并借助遗传算法(GA)求解目标参数,实现翼伞系统能量控制及逆风着陆.提出的复杂环境下翼伞系统的组合式航迹规划策略求解速度较快,能够同时满足翼伞系统避障、能量控制及逆风着陆要求,得到的参考航迹较为平滑.

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. Note to Practitioners —This article was motivated by the problem of airdropping massive goods and materials. Existing methods usually adopt a single heavy parafoil, or use centralized multiparafoil systems. Both these methods have their limitations. For the former, there is an upper limit of the load capacity for a single parafoil. For the latter, the parafoils in the centralized system lack fully autonomous ability. Distributed multiparafoil systems could solve the problem effectively. However, compared to single-parafoil systems, there are still some challenges, for example, the multiparafoil gathering, collision avoidance and cooperative formation, as well as the upwind landing. Fortunately, existing parafoils are equipped with sensors, communication, and control devices, so they could be viewed as agents with autonomous capabilities. In this article, a formation guidance framework for multiple autonomous parafoils is proposed. First, we plan a trajectory for the pilot parafoil. Then, we show how to effectively track the planned trajectory. Finally, we demonstrate how multiple parafoils could coordinate with each other to accomplish airdrop tasks. The simulation results confirm the feasibility of this strategy.

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.

In large-scale natural disasters and military supplies, multiple parafoils are more capable of performing actual tasks. The cooperative paths planning for multiple parafoils with different initial positions and headings is an important step in multiple parafoils airdrop, which has to satisfy multiple objectives, namely, parafoils can’t collide with each other, parafoils should rendezvous at same target area, most of parafoils need to keep alignment against wind, and planned paths should be in the range of maneuver performance constraints to ensure that every parafoil’s path is flyable. Due to more factors need to be considered, it is more difficult to plan paths for multiple parafoils than single parafoil. In this paper an improved genetic algorithm is used to solve the multi-objective cooperative paths planning problem of multiple parafoils system. Parafoils’ paths are encoded by real matrix, and the cooperative relationship between parafoils is realized by paths fitness function. The random single point crossover and Gaussian mutation are introduced to accelerate algorithm convergence rate. Finally, a simulation example is given, simulation results show that proposed method can plan feasible paths for all parafoils, meanwhile, it satisfies the requirements of anti-collision, rendezvous to target point, and keep alignment against the wind.

使用北京人工影响天气办公室提供的2014-2017年京津冀地区飞行记录积冰个例样本与机载观测数据,2016年全国空中报告积冰、非积冰个例样本和欧洲中期天气预报中心(ECMWF)第5代全球气候大气再分析数据(ERA5),基于模糊逻辑隶属度函数,定义了以气温和相对湿度为判别基础并考虑垂直速度和云量影响的积冰指数Ip(icing potential index),用于判断飞机在空中发生积冰事件的可能性.检验结果表明:该指数对积冰事件的判别准确率为80.2％,与目前国内常用的经典积冰指数(Ic)相比,其判别准确率有明显提升,且漏报率和虚警率均显著降低(分别为9.4％和10.4％),结合数值预报产品可对飞机在空中特定位置发生积冰事件的可能性进行预测.

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.

In order to implement the precise airdrop of parafoil system,the homing trajectory shoule be planned rationally. Multiphase homing trajectory is adopted according to the motion characteristics and handling characteristics of parafoil system. Based on the four degree of freedom model,objective function which can be used to evaluate trajectories is established by using the geometrical relationship of each trajectory segment. Getting the global optimal solution of the objective function by means of improved Artificial fish swarm algorithm,then the design parameters of the trajectory are obtained. The simulation results show that this improved method can accelerate the convergence speed of the algorithm,and the planning trajectory meet the demands of precise airdrop and upwind landing.

Aiming at altitude-keeping of a tilt tri-rotor UAV in flight mode conversion,a new transition strategy was proposed,by which the UAV could implement the transition directly from hovering state without requiring an initial velocity.The Newton-Euler method was adopted for dynamics modeling of the transition mode.The relationship between tilting angle and flight speed,i.e.,the corridor curve of transition mode,was obtained according to the model analysis.Flight test was made to two different tilting modes by using the experimental prototype of tilt tri-rotor UAV.Analysis to the telemetering data obtained from ground station shows that the corridor curve of transition mode is effective for altitude-keeping.

首先建立翼伞六自由度的模型,利用最优控制理论,分别采用时间最优控制、能量最优控制以及相应的改进控制算法对翼伞空投控制技术进行比较研究.并提出以高度作为判断准则的系统归航方案,分别对比在不同的高度下,各控制方法的优缺点及适用性.在此基础上运用Simulink仿真验证不同高度下的最佳规划航迹,最终为实际翼伞的投放提供理论基础.

当前对翼伞系统的研究主要集中在单个翼伞,但实际空投中一般需要使用多个翼伞,才能完成大量物资、装备的空投补给任务,而多个翼伞同时空投时,将会出现翼伞需要集结、相互间需要避免碰撞等在单翼伞空投时不存在的问题.现有的单翼伞系统已能通过GPS/惯导系统及其他板载传感器实现自主飞行,针对多个自主翼伞的空投任务设计算法,以控制下降翼伞之间的相互运动,实现多翼伞系统的集结和避碰.首先以质点模型为起点,通过引入新的独立变量,并将翼伞运动转换至风固定坐标系,使得单个翼伞质点模型降维为非线性降阶模型,进而得到多自主翼伞模型,在此基础上提出了一种集结控制算法,利用每个翼伞自身的状态信息和相邻翼伞的状态信息,采用势场法使得多翼伞实现集结并避免碰撞,最后一致地降落至地面.仿真结果表明多个自主翼伞实现了集结,减小了翼伞的着陆散布,降低了翼伞之间的碰撞风险,验证了该方法的有效性,可以为进一步研究多自主翼伞协同控制提供理论参考.

An improvement project of displacement sensor experiment system was put forward. A micro-stepper motor was used to control the displacement. The subdivision control strategy was adopted to keep it running smoothly. The stepping motor driving system adopted 3957. AT89C52 SCM was used as centre controller,and AD574 was used as AD converter,LCD 1602 and freestanding button were used as man-machine interface The new system not only could achieve the original purpose,but also could improve experiment efficiency and the credibility of the experimental data.Thus the limited in-class experimental class hours were saved,Experimental capacity was expanded and its quality was improved.