A novel trajectory planning strategy for aircraft emergency landing using Gauss pseudospectral method

To improve the survivability during an emergency situation, an algorithm for aircraft forced landing trajectory planning is proposed. The method integrates damaged aircraft modelling and trajectory planning into an optimal control framework, in order to deal with the complex aircraft flight dynamics, a solving strategy based on Gauss pseudospetral method （GPM） is presented. A 3-DOF nonlinear mass-point model taking into account the wind is developed to approximate the aircraft flight dynamics after loss of thrust. The solution minimizes the forced landing duration, with respect to the constraints that translate the changed dynamics, flight envelope limitation and operational safety requirements. The GPM is used to convert the trajectory planning problem to a nonlinear programming problem （NLP）, which is solved by sequential quadratic programming algorithm. Simulation results show that the proposed algorithm can generate the minimum-time forced landing trajectory in event of engine-out with high efficiency and precision.     

Automating Human Thought Processes for a UAV Forced Landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system.     

Reachability Analysis of Landing Sites for Forced Landing of a UAS

This paper details a method to ascertain the reachability of known emergency landing sites for any fixed wing aircraft in a forced landing situation. With a knowledge of the aircraft’s state and parameters, as well as a known wind profile, the area of maximum glide range can be calculated using aircraft equations of motion for gliding flight. A landing descent circuit technique used by human pilots carrying out forced landings called high key low key is employed to account for the extra glide distance required for an approach and landing. By combining maximum glide range analysis with the descent circuit, all the reachable landing sites can be determined. X-Plane flight simulator is used to demonstrate and validate the techniques presented.     

基于能量管理的飞翼飞行器迫降轨迹设计

针对飞翼类飞行器迫降轨迹设计问题,建立力学运动模型对无动力滑翔过程进行分析,采用满足始末端约束和飞行器性能约束的Dubins轨迹进行轨迹搜索,并提出根据迫降初始能量状态采用广义Dubins类型航线规划低能迫降轨迹和高能迫降轨迹。通过批量仿真验证了迫降飞行阶段分段管理和能量实时评估实现迫降轨迹设计的方法使飞行器精确回收到迫降点的同时兼具适应环境干扰的鲁棒性,对实际工程应用具有重要意义。     

Application of generalised neural network for aircraft landing control system

 It is observed that landing performance is the most typical phase of an aircraft performance. During landing operation the stability and controllability are the major considerations. To achieve a safe landing, an aircraft has to be controlled in such a way that its wheels touch the ground comfortably and gently within the paved surface of the runway. The conventional control theory found very successful in solving well defined problems, which are described precisely with definite and clearly mentioned boundaries. In real life systems the boundaries can't be defined clearly and conventional controller does not give satisfactory results. Whenever, an aircraft deviates from its glide path (gliding angle) during landing operation, it will affect the landing field, landing area as well as touch down point on the runway. To control correct gliding angle (glide path) of an aircraft while landing, various traditional controllers like PID controller or state space controller as well as maneuvering of pilots are used, but due to the presence of non-linearities of actuators and pilots these controllers do not give satisfactory results. Since artificial neural network can be used as an intelligent control technique and are able to control the correct gliding angle i.e. correct gliding path of an aircraft while landing through learning which can easily accommodate the aforesaid non-linearities. The existing neural network has various drawbacks such as large training time, large number of neurons and hidden layers required to deal with complex problems. To overcome these drawbacks and develop a non-linear controller for aircraft landing system a generalized neural network has been developed.     

Apollo lunar descent guidance

Apollo Lunar-descent Guidance transfers the Lunar Module from a near-circular orbit to touchdown, traversing 17° central angle and 15 km altitude in 11 min.A group of interactive programs in an onboard computer guide the descent, controlling altitude and the descent propulsion system throttle. A ground-based program precomputes guidance targets.This paper describes the concepts involved. Explicit and implicit guidance are discussed, guidance equations are derived, and the earlier Apollo explicit equation is shown to be an inferior special case of the later implicit equation. The paper describes interactive guidance by which the two-man crew selects a landing site in favorable terrain and directs the trajectory there. Interactive terminal-descent guidance enables the crew to control the essentially vertical descent rate in order to land in minimum time with safe contact speed. The attitude maneuver routine uses concepts that make gimbal lock inherently impossible. The throttle routine yields zero steady-state thrust-acceleration error or avoids operation within a thrust region forbidden because of hardware limitations. The ground-based program precomputes guidance targets which shape the trajectory to produce an efficient descent with adequate visibility and no transients at the final phasic interface.     

一种基于视觉的飞行器接近角估计方法

提出了一种基于图像序列的飞行器接近角的估计方法.飞行器的接近角对于飞行器的着陆来说是一个非常重要的参数,是指飞行器在着陆时的飞行轨迹与地平面之间的夹角.飞行器在着陆时近似作平移运动,在这种情况下,图像上的极点称作FOE(focus-of-expansion),地平面的消失线被称作Horizon.首先给出了从已标定的图像序列中提取FOE和Horizon的方法,然后由这两个参数估计出飞行器的接近角.模拟实验和真实图像实验表明该方法是可行的.     

基于单步最优方法的推力矢量垂直短距飞机过渡过程控制

推力矢量垂直短距起降飞机(V/STOL)具有巡航速度快和起降灵活的特点,近年来受到了广泛的关注.然而,该型飞机需要经历悬停转平飞和平飞转悬停的过渡过程阶段,期间飞机会面临强耦合、强非线性等控制难题,使得传统控制器难以胜任.针对上述问题,通过充分考虑执行器的执行能力,提出一种基于单步最优方法的过渡过程控制策略.所提方法结合推力矢量V/STOL飞机的特点,在确保飞机姿态可控的前提下使飞机水平加速度最大,同时使三轴承推力矢量喷管转角向目标转角不断靠近,从而以最快的速度完成过渡过程,并进行控制器切换.仿真实验验证了所提方法具有过渡过程时间短、姿态平稳的优点.     

Pilot performance, strategy, and workload while executing approaches at steep angles and with lower landing minima

OBJECTIVE: We examined the willingness and ability of general aviation pilots to execute steep approaches in low-visibility conditions into nontowered airports. BACKGROUND: Executing steep approaches in poor weather is required for a proposed Small Aircraft Transportation System (SATS) that consists of small aircraft flying direct routes to a network of regional airports. METHOD: Across two experiments, 17 pilots rated for Instrument Flight Rules at George Mason University or Virginia Tech flew a Cessna 172R simulator into Blacksburg, Virginia. Pilots were familiarized with the simulator and asked to fly approaches with either a 200- or 400-foot ceiling (at approach angles of 3 degrees, 5 degrees, and 7 degrees in the first experiment, 3 degrees and 6 degrees in the second). Pilots rated subjective workload and the simulator recorded flight parameters for each set of approaches. RESULTS: Approaches with a 5 degree approach angle produced safe landings with minimal deviations from normal descent control configurations and were rated as having a moderate level of workload. Approaches with 6 degree and 7 degree approach angles produced safe landings but high workload ratings. Pilots reduced power to control the speed of descent and flew the aircraft slightly above the glide path to gain time to control the landing. CONCLUSION: Although the 6 degree and 7 degree approaches may not be practical for routine approaches, they may be achievable in the event of an emergency. APPLICATION: Further work using other aircraft flying under a wider variety of conditions is needed before implementing SATS-type flights into airports intended to supplant or complement commercial operations in larger airports.     

考虑基站选址的UAV交通巡视路径超级时空网络模型

针对考虑基站选址的无人机交通巡视路径优化问题,提出一个超级网络与时空网络相结合的方法,并通过该方法建立模型。通过在时空网络添加虚拟起降点,与全部时刻的备选基站相连接构成超级时空网络,可将考虑基站选址的路径规划转换为一个单纯的多UAV路径规划问题。与不考虑基站选址的路径规划相比,考虑基站选址能够使最大单机飞行时间和总飞行时间分别减少5.71%和11.59%。数值分析表明,基站选址和交通巡视路径规划整合可有效减少UVA的巡视成本。     

基于区域行进策略的飞机油箱检查机器人路径规划算法

针对类似于飞机油箱环境中连续型机器人的路径规划问题,设计基于区域行进策略的路径规划算法,结合机器人本体结构约束规划到达油箱内任意给定目标点的路径。连续型机器人具有运动灵活性,但超冗余自由度导致了三维空间规划的多解性,增加了算法的复杂度。采用降低维度的方式,通过将三维空间转化为二维平面进行规划,降低了算法的时间复杂度。将飞机油箱的单舱划分为两个区域,根据目标点所处区域位置确定规划策略。最后,基于Matlab对所提算法进行仿真,实验结果验证了算法的可行性和有效性。     

Adaptive trajectory generation based on real-time estimated parameters for impaired aircraft landing

ABSTRACT

This paper is motivated by a need to address the challenge of securing a safe landing after suffering from inflight impairment. In this paper, a new adaptive generalised model predictive static programming (G-MPSP) is developed to generate a safe emergency landing trajectory for impaired aircraft. Utilising the computationally efficient G-MPSP framework, the proposed algorithm enables adaptation of model parameters based on the prediction errors to ensure reasonable guidance performance. Based on the estimated parameters, a feasible landing trajectory is then generated by the flexible finite-horizon G-MPSP with input constraints. The integrated approach features explicit closed-form solutions for both parameter estimation and trajectory generation. Its effectiveness is demonstrated by simulations in the presence of parameter uncertainties and noises and by comparison studies with the non-adaptive G-MPSP.     

飞机起飞调运航路规划方法研究

针对飞机从停机位到起飞位的调运航路规划问题,为了规划最优航路,首先采用栅格法建立了飞行场地和飞机的简化模型,根据飞行场地的飞机布列位置,应用蚁群优化算法,规划出所有飞机从停机位到不同的起飞位的调运航路;针对飞机运动时的转角约束条件,利用B样条对规划出的调运航路进行平滑处理。经仿真生成了安全、可行的最短调运航路。仿真结果表明,将蚁群算法和B样条相结合应用于飞机调运航路规划,可以满足飞机运动的约束条件且规划出的结果优化。     

基于改进蚁群与动态窗口法的AGV动态路径规划

针对全局静态路径规划算法无法有效躲避动态障碍物、局部动态路径规划算法缺少全局环境信息指导规划路径质量差或无法成功到达目标点等问题,提出了一种结合改进蚁群算法和动态窗口法的全局动态路径规划算法,实现在动态环境中的全局最优路径实时规划.对传统蚁群算法提出了初始信息素不均匀、双向分布、引入放大系数A增大相邻栅格启发信息差异、...     

基于IBA-LSSVM强迫选择模型的民用飞机着陆滑行仪表灯常亮故障关联检测

民用飞机着陆滑行仪表灯是故障检测系统的重要组成部分，因民用飞机在地面滑行过程中，电气接口易受到电磁干扰，引起着陆滑行仪表灯常亮故障，在飞行过程中增加了安全隐患。为此，提出引入IBA-LSSVM强迫选择模型的民用飞机着陆滑行仪表灯常亮故障关联检测方法。分析仪表灯常亮故障产生的原因，利用Python编程数据采集飞机起飞、近进、降落、地面滑行时的照明信号及电气交联数据，通过控制逻辑，建立数据关联检测逻辑关系数据库。利用自适应多普勒补偿方法改进蝙蝠算法（IBA），检测着陆滑行灯常亮故障特征，在强迫选择部分，构建IBA-LSSVM模型，将分布式博弈和线性输出调节理论相结合，抵消外部干扰，完成着陆滑行灯常亮故障检测。Matlab仿真测试结果表明：所提方法的故障识别率均在95%以上，故障识别准确率可以达到97.3%，故障识别时间低于2ms，可有效识别故障数据，降低飞行安全隐患。     

基于某型雷达的着陆航迹纠偏监控研究

为了减少飞机着陆阶段的飞行事故,基于某型精密进场雷达设计了飞机着陆航迹纠偏监控设备;通过研究某型雷达的回波数据格式和传输要求,在Windows环境下,采用Microsoft Visual Studio 10.0开发工具,用C#语言开发了着陆航迹纠偏监控软件;该软件能实时、自动监控加入着陆航线的多批次飞机的着陆航迹数据,对超出安全着陆要求的飞机按不同着陆等级设置三类告警门限,在超限事件引发严重事故之前,实时提醒地面人员指挥引导飞机切入安全合适的下滑道进行着陆,解决了某型雷达完全依赖人工监视飞机着陆状态的缺陷;同时,软件可对雷达数据包进行实时采集和误差分析,以作为日常飞行训练质量的辅助分析手段和飞行事故的调查依据。     

飞行器分层势场路径规划算法

传统势场法是飞行器路径规划的一种常用方法,但是存在目标不可达、易收敛到局部极小值和无评价机制等问题.本文针对这些问题提出了一种飞行器路径规划的分层势场算法.利用分段思想对势场函数进行修正,解决了目标不可达问题.引入回环力和飞行器间作用力,解决了易收敛到局部极小值问题和飞行器间的碰撞问题.采用分层方法,建立了多层次多方位路径点阵,并以此计算最优路径点,从而引入了势场法的评价机制.通过数值仿真,对在复杂障碍环境中的飞行器路径规划进行了传统势场法、改进势场法和分层势场法的对比研究.仿真结果验证了所提出的分层势场算法的有效性和可行性.     

On‐line estimation and path planning for multiple vehicles in an uncertain environment

A unified approach to cooperative target tracking and path planning for multiple vehicles is presented. All vehicles, friendly and adversarial, are assumed to be aircraft. Unlike the typical target tracking problem that uses the linear state and nonlinear output dynamics, a set of aircraft nonlinear dynamics is used in this work. Target state information is estimated in order to integrate into a path planning framework. The objective is to fly from a start point to a goal in a highly dynamic, uncertain environment with multiple friendly and adversarial vehicles, without collision. The estimation architecture proposed is consistent with most path planning methods. Here, the path planning approach is based on evolutionary computation technique which is then combined with a nonlinear extended set membership filter in order to demonstrate a unified approach. A cooperative estimation approach among friendly vehicles is shown to improve speed and routing of the path. Copyright © 2004 John Wiley & Sons, Ltd.     

Minimum energy oriented global stabilizing control of the PVTOL aircraft

A global stabilizing control law is proposed for a non-minimum phase under-actuated planar vertical take-off and landing (PVTOL) aircraft. The proposed approach is based on receding horizon control and takes into account the positiveness of the thrust and its saturation to any arbitrary level. Moreover, the angular acceleration can also be bounded. Contrary to non-linear optimal control, the proposed approach, based on quadratic programming, improves significantly the computational cost of the algorithm and the convergence to a solution can be insured. The chosen cost function has a direct link with the energy needed to reach a desired point which is one of the main worries in the design of embedded control systems such as micro unmanned aerial vehicles (UAV).