亚轨道飞行器任务中止再入轨迹优化设计

针对亚轨道飞行器上升段由于动力故障任务中止时再入返回的问题,考虑飞行模型简化和故障后的燃料处理方案,通过遗传算法优化设计最优返回轨迹,优化时选取经向飞行航程最远作为性能指标,并采用遗传算法,解决用于再入轨迹优化所涉及的关键问题,并进行仿真。仿真结果表明,方法不但满足飞行器返回过程中加热率、过载、动压约束以及终端状态约束,能够通过飞行航程最远消耗飞行器能量从而安全着陆,而且可以较快地搜索到全局最优解,能够用于亚轨道飞行器故障再入轨迹的优化设计。     

混合编码差分进化算法求解含邻域Dubins旅行商问题

含邻域Dubins旅行商问题(DTSPN)是一个具有挑战性的混合变量优化问题,它源于Dubins车的运动规划,例如轨迹受曲率约束的高速飞行器.本文在对DTSPN的相关研究进行综述的基础上,提出两种混合编码差分进化算法来有效求解DTSPN,这两种算法分别采用完整编码方案和部分编码方案.完整编码差分进化算法在整个解空间中搜索最优的Dubins路径,有利于充分探索搜索空间.通过对Dubins车在相邻两点间移动时的终端朝向进行松弛,本文提出一种部分编码差分进化算法,在解的质量和计算时间方面实现了较好的权衡.比较性计算实验包含两种差分进化算法以及现有文献中的两种先进DTSPN算法,实验结果表明基于终端朝向松弛和部分编码的差分进化算法能够以较小的计算代价得到DTSPN的高质量解,明显优于其他算法.     

基于改进粒子群算法的再入飞行器轨迹优化

采用基于距离量度和自适应惩罚相结合的约束处理技术的改进粒子群优化算法(PSO)应用于再入飞行器轨迹优化,避免适应值函数中复杂的罚函数及罚因子的设计,提高优化算法的通用性.以高超声速飞行器最小控制量再入轨迹优化为例,并对飞行器运动模型进行简化及控制量参数化.对两种不同的高超声速飞行器模型进行优化,仿真结果验证算法的有效性...     

基于倾斜角控制的飞行器区域规避轨迹规划

高速飞行器通过改变航向角的方式来进行转弯,导致转弯半径很大,影响机动性,针对这一问题提出了基于倾斜角控制转弯的轨迹设计方法,保证了转弯半径尽可能的小,增加了飞行器的机动性能。首先根据飞行动力学原理进行动力学建模,然后对飞行器再入过程中的动压、过载、热流等物理约束进行了建模,并考虑了平衡滑翔约束,进而通过将各类不等式过程约束转化为轨迹控制量倾斜角的约束,实现了在满足过程约束的条件下,以较小的转弯半径成功规避区域障碍。数值仿真结果表明,该方法比单纯几何规划更精确,所设计的轨迹便于飞行器控制系统进行跟踪,具有实际工程参考意义。     

三维自主再入制导方法

基于阻力加速度-能量剖面设计,提出一种新的三维自主再入制导方法.该方法的阻力加速度-能量剖面由再入走廊上边界和下边界内插得到,倾侧角采用两次反转模式,轨迹规划同时考虑了飞行器的纵向和横向运动,并具有在线生成三维轨迹的能力.最后对制导方法的适应性进行了仿真分析,仿真结果表明给出的再入制导方法能适应不同情况的再入,使飞行器在具有较好轨迹特性的同时以较高的精度到达末端能量管理界面.     

基于Dubins曲线的无人直升机轨迹规划

为提高无人直升机的控制性能,提出了一种基于Dubins曲线的轨迹规划算法,并对其各个部分的实现进行了研究和设计。该算法利用Dubins曲线原理对定点飞行任务的两点或者多点目标进行分析计算,寻找出一条最短的飞行路径,从而提高了飞行效率。根据无人直升机系统多变量、非线性和强耦合的特点,采用串级PID方法设计了飞行控制器,该控制器能够修正无人直升机的姿态和位置,从而提高了轨迹规划的稳定性和准确性。最后,以某小型无人直升机为实验平台表明了该轨迹规划算法和控制器的可行性。     

基于反席卷法的高超声速飞行器最优制导律

针对高超声速飞行器再入制导过程中,对轨迹重新优化产生的大计算量导致难以在线实施的问题,采用逆向席卷法设计了一种实时的标称最优制导律.建立了轨迹优化模型,采用伪谱法求解了满足多种路径约束与终端约束的标称最优轨迹.考虑消除扰动所形成的实际修正轨迹的最优性,采用逆向席卷法推导了存在初始扰动的条件下快速求解最优修正轨迹的反馈控制量,构成了可以闭环在线实施的最优制导律.仿真结果表明,所设计的制导律对飞行器初始状态量的较大范围偏差具有良好的鲁棒性,并且能够满足实时性的要求.     

基于SEAD任务特性约束的协同任务分配方法

以多异构无人机执行SEAD任务为背景,开展协同任务分配问题建模、算法设计和仿真分析.采用图论的方法完成问题的建模,将无人机本体等效为Dubins Car模型,并对其在相应目标处执行侦查、打击、评估任务时的进入角度进行约束,通过Dubins路径完成对无人机飞行路径的等效,采用分布式遗传算法完成对问题的快速求解.研究结果表明,带有路径末端角度约束的任务分配问题具有较好的实用意义,分布式遗传算法可有效处理实时任务分配问题,完成任务空间的快速决策.     

基于滑模控制的导弹制导系统设计

对传统的导弹制导系统进行改进设计,改善导弹的路径跟踪效果。首先引入Dubins曲线对导弹进行航迹规划进行,并基于滑模控制进行导弹制导策略的设计,自动驾驶仪系统采用级联比例积分控制器。Dubins曲线能为导弹创建更平滑的参考轨迹,减少导弹的超冲运动与振荡现象。滑模控制通过计算导弹与参考轨迹的相对距离,获得参考方位角,进而实现对参考轨迹的跟踪,能够提高制导系统响应速度、抗干扰能力。对导弹跟踪路径效果进行仿真,对比引入dubins曲线前后导弹的跟踪轨迹的误差与振荡现象,证明了引入dubins曲线对于导弹的路径规划工作具有显著帮助,并对结果中的一些现象进行了讨论。并已dubins曲线作为仿真路径,对传统比例制导策略和改进型滑模控制制导策略的仿真结果进行对比,证明了改进型制导系统设计的可行性,并对其路径跟踪表现的特点进行了讨论。     

高超声速飞行器飞行轨迹的模糊控制设计

针对高超声速飞行器飞行过程中因干扰造成的飞行轨迹散布问题,提出了采用飞行器飞行轨迹的模糊控制设计方法。方法以高超声速飞行器飞行轨迹线偏差和线偏差变化率作为模糊控制器输入,采用模糊推理设计飞行控制系统。在完成高超声速飞行轨迹控制系统数学建模的基础上,结合自动驾驶仪特点对飞行轨迹模糊控制系统进行了设计。结论通过仿真表明所设计的飞行控制系统满足飞行轨迹及攻角性能要求,验证了方法的正确性。     

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.     

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.     

Autolanding a Power-off UAV Using On-line Optimization and Slip Maneuvers

This paper tackles the final stages of autolanding a fixed-wing Unmanned Air Vehicle (UAV) in a power-fail emergency scenario. We applied the principle of Nonlinear Model Predictive Control (NMPC) to plan trajectories that respect the aircraft’s limits, and react on disturbances and environmental changes in real-time. However, thanks to judicious problem formulations, our algorithm optimizes—in each time step—the whole horizon of the landing trajectory, and settles a dynamic compromise between the different touchdown requirements. Furthermore, the algorithm is powered by a novel method that utilizes slip maneuvers to achieve adequate energy control notwithstanding the absence of specialized drag control devices. Thus, precise touchdown point is attained even in the presence of strong wind shear and large initial errors. All design parameters are optimized off-line over a wide spectrum of conditions using Genetic Algorithm (GA). Monte-Carlo simulation of the optimized design shows excellent landing performance and high success rate on both flat and sloping terrains.     

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.     

舰载机纵向容错着舰系统设计

通常发生的舰载机着舰事故中,大多数是由于舰载机纵向航迹控制不好导致的,而造成航迹控制性能下降的最主要因素是航母运动、舰尾流扰动和执行器故障.针对这些特殊情况,提出了一种容错控制方法,应用在纵向着舰系统中.首先采用基于非线性动态逆的滑模控制方法抑制舰尾流扰动影响,然后在此基础上,加入径向基神经网络,利用其对非线性项的万能逼近特性,来补偿执行器故障情况下造成的系统故障,进一步保证了舰载机对理想下滑道的精确跟踪,最后,加入不同类型的执行器故障对此方法进行测试.仿真结果表明,所设计的纵向容错着舰系统不仅具有较强的鲁棒性和容错能力,而且提高了舰载机着舰航迹控制精度.     

垂直起降飞机的全局轨迹跟踪控制

研究垂直起降飞机在任意输入耦合作用下的轨迹跟踪控制问题．垂直起降飞机是具有3个自由度、2个控制输入的欠驱动系统．首先通过控制输入和坐标变换，使飞机的动力学方程变换成严格反馈形式；然后基于后推法的思想推导出保证系统渐近收敛于参考轨迹的时变反馈控制规律．该方法将系统分解为低阶子系统来处理，利用中间虚拟控制变量和部分Lyapunov函数筒化了控制器的设计．仿真结果表明所设计的控制器是有效的．     

Landing Auto‐Pilots for Aircraft Motion in Longitudinal Plane using Adaptive Control Laws Based on Neural Networks and Dynamic Inversion

This paper presents two new automatic landing systems (ALSs) for aircraft motion in longitudinal plane; the model of the landing geometry determines the flight trajectory and the aircraft calculated altitude; the flight trajectory during landing consists of two parts: the glide slope and the flare. Both designed ALSs have an adaptive system (ACS) for the aircraft output's control; for the first ALS, the output vector consists of the flying altitude and the longitudinal velocity, while, for the second ALS, the output variables are the pitch angle and the longitudinal velocity of aircraft. The second variant of ALS also contains an altitude controller providing the calculated pitch angle. The calculated altitude (for the first ALS), the calculated pitch angle (for the second ALS), and the desired flight velocity are provided to the ACS by means of a block consisting of two reference models. ACS is based on the dynamic inversion concept and contains an adaptive controller which includes a linear dynamic compensator, a state observer, a neural network, and a Pseudo Control Hedging block. The paper is focused both on the design of the two ALSs and on their complex software implementation and validation.     

Three-dimensional trajectory optimization of soft lunar landings from the parking orbit with considerations of the landing site

Minimum fuel, three-dimensional trajectory optimization from a parking orbit considering the desired landing site is addressed for soft lunar landings. The landing site is determined by the final longitude and latitude; therefore, a two-dimensional approach is limited and a three-dimensional approach is required. In addition, the landing site is not usually considered when performing lunar landing trajectory optimizations, but should be considered in order to design more accurate and realistic lunar landing trajectories. A Legendre pseudospectral (PS) method is used to discretize the trajectory optimization problem as a nonlinear programming (NLP) problem. Because the lunar landing consists of three phases including a de-orbit burn, a transfer orbit phase, and a powered descent phase, the lunar landing problem is regarded as a multiphase problem. Thus, a PS knotting method is also used to manage the multiphase problem, and C code for Feasible Sequential Quadratic Programming (CFSQP) using a sequential quadratic programming (SQP) algorithm is employed as a numerical solver after formulating the problem as an NLP problem. The optimal solutions obtained satisfy all constraints as well as the desired landing site, and the solutions are verified through a feasibility check.