Particle swarm optimization applied to hypersonic reentry trajectories

This paper presents the novel use of the particle swarm optimization(PSO)to generate the end-to-end trajectory for hypersonic reentry vehicles in a quite simple formulation.The velocitydependent bank angle profile is developed to reduce the search space of unknown parameters based on the constrained PSO algorithm.The path constraints are enforced by setting the fitness function to be infinite on condition that the particles violate the maximum allowable values.The PSO algorithm also provides a much easier means to satisfy the terminal conditions by adding penalty terms to the fitness function.Furthermore,the approximate reentry landing footprint is fast constructed by incorporating an interpolation model into the standardized bank angle profiles.Numerical simulations demonstrate that the PSO method is a feasible and flexible tool to generate the end-to-end trajectory and landing footprint for hypersonic reentry vehicles.     

多滑翔飞行器时间协同轨迹快速规划

从高超声速飞行器集群"探测-打击-评估"一体化任务需求出发,针对多滑翔飞行器时间协同再入轨迹规划问题进行研究,提出集群再入的协同形式及轨迹规划方案,基于改进序列凸化算法解决了再入总飞行时间的精确控制问题,从而实现滑翔段时间协同。首先,给出了滑翔飞行器集群的协同策略,将求解模型转化为协同时间的确定、协同时间约束下的轨迹规划子问题。将模型中的时间项误差等加入罚函数,提高了协同轨迹求解可行性。引入飞行路径角预设剖面作为软约束,并通过罚函数与信赖域自适应调整,以避免轨迹求解时的振荡问题,提高了序列凸化算法的收敛性。以CAV-H飞行器模型为例验证了算法的有效性,仿真结果表明,所提算法对初值的敏感性低,求解得到的再入总时间可调范围与伪谱法一致,轨迹规划结果的平滑性及计算时间均优于伪谱法。     

基于改进的粒子群优化算法的无人作战飞机航路规划

事先针对敌方防御区内的威胁部署和目标的分布情况,对无人作战飞机的飞行航路进行整体规划设计,可以综合减小被敌方发现和反击的可能性、降低耗油量,从而显著提高UCAV执行对地攻击(或侦察)任务的成功率.在对粒子群优化技术研究的基础上,将一种用于解决TSP的PSO算法加以改进,引入模拟退火的策略思想,借以克服PSO算法易陷局部最优的早熟现象,并在UCAV航路规划中加以运用.仿真实验表明,该算法简易而有效,用其优化出的航路能够满足UCAV飞行任务规划的需要.     

基于改进一致性算法的无人机编队控制

编队飞行是指多架无人机保持以一定队形进行飞行的状态,相比于单架飞机执行任务,无人机编队能够增加搜索面积,提高飞机飞行性能,增大完成任务成功率。编队控制是实现编队安全高效完成指定任务的前提。本文以一致性理论为基础,针对无人机运动模型的特点与实际飞行要求,对基本的一致性算法进行改进,提出了改进一致性无人机编队控制算法。首先利用纵向和横侧向解耦的自动驾驶仪模型给出了无人机的三自由度运动方程,根据机动性与飞行性能要求定义了各方向上的加速度、速度与角速度约束。基于一致性理论,将编队控制分为平面与纵向2个方向进行,在状态控制的基础上,利用各状态变量间的几何关系对无人机运动自由度进行转换,加入编队队形信息,设计了编队控制算法。为了使算法生成的指令信号满足约束条件,提出了"最小调整"约束条件处理策略。依据粒子群算法对各无人机的爬升加速度进行优化,以避免机间碰撞。仿真结果表明：提出的编队控制算法具备编队成形与变换功能,能够使无人机编队状态快速收敛到指定值,且保持指定队形,无人机飞行状态满足所有约束条件。     

多植保无人机协同路径规划

为实现多植保无人机（UAVs）协同作业，并提高作业效率，提出了一种基于改进粒子群优化（PSO）的多植保无人机协同路径规划算法。根据作业区域的形状面积和植保UAV的作业参数划分各架UAV作业区域，采用栅格法生成各区域全覆盖作业航线。以各架植保UAV各架次植保作业距离为算法寻优变量，在确保各架UAV补给时间满足间隔分布约束条件下，综合考虑补给总次数、返航补给总时间、总耗时和最小补给时间间隔4项因素，并构成目标函数，通过采用改进PSO算法，实现了对各UAV返航顺序和返航点位置的寻优。仿真分析结果表明，相较于最大作业距离规划和最小返航距离规划，本文提出的规划算法表现出了较优的性能和较好的作业区域适应性，证实了其有效性和实用性。     

基于改进鸽群算法的高超声速飞行器轨迹优化

采用基于罚函数思想的约束处理技术改进鸽群智能算法,应用于复杂的带约束的飞行器轨迹优化问题。以高超声速飞行器爬升段轨迹优化为例,建立其包含微分方程约束、路径约束和终端约束的优化数学模型,通过罚函数构造算法的适应值函数并对优化变量添加边界强约束,将改进的鸽群智能(PIO)算法和粒子群(PSO)算法对高超声速飞行器爬升段优化数学模型进行对比仿真分析。仿真结果表明,改进的鸽群智能算法在解决此类复杂带约束优化问题中展现出了更好的优化效率,具有良好的工程应用价值。     

Autonomous gliding entry guidance with geographic constraints

This paper presents a novel three-dimensional autonomous entry guidance for relatively high lift-to-drag ratio vehicles satisfying geographic constraints and other path constraints. The guidance is composed of onboard trajectory planning and robust trajectory tracking. For trajectory planning, a longitudinal sub-planner is introduced to generate a feasible drag-versus-energy profile by using the interpolation between upper boundary and lower boundary of entry corridor to get the desired trajectory length. The associated magnitude of the bank angle can be specified by drag profile, while the sign of bank angle is determined by lateral sub-planner. Two-reverse mode is utilized to satisfy waypoint constraints and dynamic heading error corridor is utilized to satisfy no-fly zone constraints. The longitudinal and lateral sub-planners are iteratively employed until all of the path constraints are satisfied. For trajectory tracking, a novel tracking law based on the active disturbance rejection control is introduced. Finally, adaptability tests and Monte Carlo simulations of the entry guidance approach are performed. Results show that the proposed entry guidance approach can adapt to different entry missions and is able to make the vehicle reach the prescribed target point precisely in spite of geographic constraints.     

Flight trajectory optimization of sun-tracking solar aircraft under the constraint of mission region

The optimal yawing angle of sun-tracking solar aircraft is tightly related to the solar azimuth angle, which results in a large arc flight path to dynamically track the sun position. However, the limited detection range of payload usually requires solar aircraft to loiter over areas of interest for persistent surveillance missions. The large arc sun-tracking flight may cause the target area on the ground to be outside the maximum coverage area of payload. The present study therefore develops an optimal flight control approach for planning the flight path of sun-tracking solar aircraft within a mission region. The proposed method enables sun-tracking solar aircraft to maintain the optimal yawing angle most of the time during daylight flight, except when the aircraft reverses its direction by turning flight. For a circular region with a mission radius of 50 km, the optimal flight trajectory and controls of an example Λ-shaped sun-tracking solar aircraft are investigated theoretically. Results demonstrate the effectiveness of the proposed approach to optimize the flight path of the sun-tracking aircraft under the given circular region while maximizing the battery input power. Furthermore, the effects of varying the mission radius on energy performance are explored numerically. It has been proved that both net energy and energy balance remain nearly constant as the radius constraint varies, which enables the solar aircraft to achieve perpetual flight at almost the same latitude as the large arc flight. The method and results presented in this paper can provide reference for the persistent operation of sun-tracking solar aircraft within specific mission areas.     

基于细菌觅食性的改进粒子群优化算法翼型设计

提出了一种基于细菌觅食性的改进粒子群优化算法。该算法以粒子群优化算法的社会模型为基础,添加了个体之间的交流项,丰富了粒子之间的优势信息源,增强了粒子的信息共享能力,同时,引入了细菌觅食算法中的趋化和驱散机制,使得算法能够有效地跳出局部最优。函数测试结果表明,该算法显著地提高了粒子群优化算法的寻优性能,并将该算法应用到了翼型设计之中。     

五种智能算法解决最大割问题分析与比较

最大割问题（Max—eulProblem）是一个典型的NP难组合优化问题。文章采用遗传算法、分布估计算法、Hopfield网络方法、蚁群算法、粒子群算法等5种算法对最大割问题进行求解,并用标准的多个不同规模最大割测试数据进行测试,研究各参数对算法的影响,并比较各种算法的时间复杂度和空间复杂度。测试结果表明该五种算法虽然在执行效率上有差异,但都能较好的解决最大割问题。     

高超声速飞行器再入多段导引方法研究

针对通用航空飞行器(CAV)的再入飞行问题,研究了一种滑翔式再入飞行器的三自由度轨迹快速生成方法。该方法将再入轨迹分为初始下降段、过渡段和占大部分飞行时间的拟平衡滑翔段,引入拟平衡滑翔条件(QEGC),将过程约束转换成倾侧角制导律的上界。结合预测校正方法在线设计满足各种轨迹约束的倾侧角制导律,最后在计算机上进行制导仿真。仿真结果表明,该方法可快速地得到满足过程约束和目标要求的弹道。     

基于阻力加速度倒数剖面的再入轨迹规划与制导方法

针对升力式飞行器再入制导问题,提出了一种基于阻力加速度倒数剖面的在线解析规划与制导方法。首先将过程和终端约束转换成阻力加速度倒数形式的飞行走廊,采用三次样条函数描述倒数剖面。然后通过解析计算航程上下界,利用待飞航程在倒数剖面内的近似线性关系,以满足待飞航程为目标,迭代计算得到阻力加速度倒数剖面;在飞行过程中根据当前状态和实际待飞航程,周期性更新阻力加速度倒数剖面。通过对阻力加速度剖面的跟踪进行纵向制导,解算倾侧角指令;通过倾侧角反向来进行侧向制导,限制航向角偏差。实现了再入轨迹的在线快速生成与更新,并利用阻力加速度动态特性,将其与跟踪制导结合,提出的方法效率高,适应性强,有工程应用的潜力。     

高超声速滑翔飞行器摆动式机动突防弹道设计

 为提高大升阻比高超声速滑翔飞行器机动突防能力,提出了一种侧向摆动式机动弹道的设计方法。基于动态逆的思想,建立了侧向摆动式机动弹道的弹道形式和所需倾侧角间的关系模型;在平衡滑翔假设下,将包括动压、过载和热流在内的飞行约束转化为迎角约束,从而确定了迎角-速度飞行走廊;在此基础上,设计了平衡滑翔情况下满足侧向摆动式机动及飞行约束所需的迎角变化规律。根据所设计的迎角和倾侧角,即可实现平衡滑翔情况下预定机动模式的侧向机动。以HTV(Hypersonic Technology Vehicle)为例进行仿真分析,结果表明该方法能够快速设计出预定机动幅度和机动频率的侧向摆动式机动突防弹道。     

A multi-strategy pigeon-inspired optimization approach to active disturbance rejection control parameters tuning for vertical take-off and landing fixed-wing UAV

In this paper, Active Disturbance Rejection Control(ADRC) is utilized in the pitch control of a vertical take-off and landing fixed-wing Unmanned Aerial Vehicle(UAV) to address the problem of height fluctuation during the transition from hover to level flight. Considering the difficulty of parameter tuning of ADRC as well as the requirement of accuracy and rapidity of the controller, a Multi-Strategy Pigeon-Inspired Optimization(MSPIO) algorithm is employed. Particle Swarm Optimization(PSO), Gen...     

Footprint Problem with Angle of Attack Optimization for High Lifting Reentry Vehicle

A formal analysis to footprint problem with effects of angle of attack (AOA) is presented. First a flexible and rapid standardized method for footprint generation is developed. Zero bank angle control strategy and the maximum crossrange method are used to obtain virtual target set; afterward, closed-loop bank angle guidance law is used to find footprint by solving closest approach problem for each element in virtual target set. Then based on quasi-equilibrium glide condition, the typical inequality reentry trajectory constraints are converted to angle of attack lower boundary constraint. Constrained by the lower boundary, an original and practical angle of attack parametric method is proposed. By using parametric angle of attack profile, optimization algorithm for angle of attack is designed and the impact of angle of attack to footprint is discussed. Simulations with different angle of attack profiles are presented to demonstrate the performance of the proposed footprint solution method and validity of optimal algorithm.     

基于社会模型改进粒子群算法的翼型优化设计

为了解决粒子群算法在寻优过程中全局最优和局部最优的矛盾,通过在粒子群算法优化过程中引入鱼类的聚群行为,发展了一种基于社会模型的改进粒子群算法。算法以粒子可视范围的不同用法为基础,提出了两种不同的优化策略,同时探讨了种群规模等参数对算法性能的影响,并通过函数测试结果证明了两种优化策略的有效性和不同的优化特性。将改进的优化算法应用在翼型的气动优化中,显著改善了翼型气动特性,提高了算法的全局搜索能力,取得了良好的优化效果。     

高超声速滑翔飞行器约束预测校正再入制导

针对大升阻比高超声速滑翔飞行器的再入制导问题,将再入轨迹划分为初始下降段、过渡段和准平衡滑翔段。初始下降段采用定倾侧角飞行,过渡段在最大倾侧角附近飞行,准平衡滑翔段利用数值预测校正方法和准平衡滑翔条件在线设计同时满足过程约束和终端约束的倾侧角制导律。通过标准条件和扰动条件下的仿真结果表明,这种制导律在满足各种约束的条件下,不仅能够达到较高的精度,而且对初始误差具有良好的鲁棒性,能够应付再入时各种不确定性因素的影响。     

空地导弹弹道增程方案设计

针对空地导弹直线对准弹道方案,采用优化初始航迹角的方法得到满足终端速度约束的弹道;最大射程飞行方案采用控制迎角的方法使航程最大,采用多项式样条插值的方法来估计迎角变化规律,用遗传算法优化采样点的参数,得到了满足终端速度约束的最大射程。通过算例对比可知,最大射程飞行方案的射程比直线对准飞行方案提高了三倍多。研究结果对空地导弹的标准弹道设计有一定的参考价值。     

空间大型机械臂系统载运轨迹优化方法

针对在搬运及组装数十吨级负载过程中,空间站用大型机械臂会对空间站载体姿态产生扰动的问题,提出了一种笛卡尔轨迹参数化方法。利用基于广义雅克比矩阵（GJM）的分解运动速度控制和优化算法来实现基座姿态扰动控制,建立了反映载体姿态变化的目标函数。基于关节运动范围及避免动力学奇异等约束,采用粒子群（PSO）算法进行目标函数的优化,有效降低了空间大型机械臂系统在搬运重型负载过程中对载体姿态的影响。仿真结果验证了算法的有效性。     

多飞行器再入段时间协同弹道规划方法

提出了一种多飞行器再入段时间协同弹道规划方法。首先,在纵向平面内规划满足航程与终端约束的纵向标称轨迹。随后,在采用轨迹跟踪律跟踪纵向标称轨迹的同时,运用考虑初始横侧向状态的多边界航向偏差角走廊策略控制飞行器的横侧向机动,以满足到达时间约束与终端约束,进而实现单枚飞行器到达时间约束下的轨迹规划。在此基础上,完成了飞行器的到达时间分布与飞行能力分析,给出了最小与最大到达时间的分析计算方法,并根据多飞行器协同再入的任务需求完成了协同飞行时间决策。最后,多飞行器协同再入与扰动条件下的仿真结果表明,该方法能够规划出满足到达时间与终端约束的协同再入轨迹,具备良好的计算精度与鲁棒性。