基于序列二次规划法优化无人机飞行性能

飞行性能优化是飞行管理系统的一项重要功能.针对间接法中,终端积分时间在迭代前后无法相同的问题,提出引入能量,将能量代替时间作为新的积分变量,用能量状态法动态地优化整个纵向飞行剖面,从而建立轨迹优化模型.模型求解时,区别于传统方法,进一步将优化模型变换成非线性规划问题,对油门推力和速度变量同时寻优,并用序列二次规划法求解.最后以某型无人机为例进行了验证,仿真结果说明,用能量状态法得到的最优速度和最优高度轨迹剖面是收敛的,有一定的工程实用价值.     

基于改进分段Gauss伪谱法的带推力高超声速 飞行器再入轨迹规划

再入轨迹规划是高超声速飞行器领域的热点问题,已吸引了众多国内外专家的关注. Gauss伪谱法以及分段Gauss伪谱法是解决含有多约束轨迹规划问题的一类有效工具.然而,发动机多次点火熄火导致推力不连续以及点火时刻控制输入的连续性要求是带推力高超声速飞行器再入轨迹优化面临的新挑战.本文将问题简化为多脉冲再入轨迹规划问题,基于改进分段Gauss伪谱法生成满足多条件约束的最优再入轨迹.通过设置分段Gauss伪谱法连续性条件,确保飞行器状态与控制输入在分段点处连续衔接.通过无动力自由再入与带推力再入算例对改进分段Gauss伪谱法进行说明,仿真结果也表明,改进分段Gauss伪谱法可有效求解带推力高超声速飞行器再入轨迹规划.     

基于SQP寻优的飞行轨迹规划方法研究

为了有效降低单位航程的燃油消耗,提出了基于SQP寻优的飞行轨迹规划方法.首先构建了适用于寻优的飞机数学模型和发动机数学模型,确定了寻优的目标函数;然后,以发动机推力范围和迎角等为约束条件,构建了寻优模型,基于SQP方法进行了飞行高度轨迹、飞行速度轨迹的寻优规划.仿真结果表明,SQP方法适用于飞机轨迹寻优规划,可以根据不同飞机起飞重量和飞行条件确定飞行高度轨迹与飞行速度轨迹,并可以明显降低飞行的燃油消耗.     

基于混合粒子群算法的远程机动轨道优化设计

研究了粒子群算法在空间飞行器连续推力轨道机动最优化问题.为优化空间飞行器轨道,给出了空间飞行器轨道机动最优化控制问题模型,运动方程用地心惯性坐标系下建立;性能指标选为轨道机动过程中时间最小;控制变量为推力攻角;终端状态受到位置和速度的约束.针对粒子群算法的缺点,提出混合粒子群算法,即将全局寻优能力强的粒子群算法和局部寻优能力强的非线性规划相结合,以提高算法的搜索精度和收敛速度.并将其应用于连续推力空间飞行器轨道机动优化之中.仿真表明混合粒子群算法对于空间飞行器远程机动轨道初始参数取值不敏感,具有一定的鲁棒性,生成的轨道能够较好地满足各种约束条件,并可以应用于空间飞行器连续推力轨道最优机动问题的求解.     

基于伪谱法的滑翔轨迹多级迭代优化策略

伪谱法可实时求解具有高度非线性动态特性的飞行器最优轨迹;以X-51A相似飞行器模型为研究对象,采用增量法与查表插值建立纵向气动力模型,伪谱法与序列二次规划算法求解滑翔轨迹最优控制问题;提出使用多级迭代优化策略,为序列二次规划算法求解伪谱法参数化得到的大规模非线性规划问题提供初值,弥补序列二次规划算法在求解大规模非线性规划问题过程中,出现的初值敏感、收敛速度减慢等问题。通过与传统方法求解出的状态量与控制量仿真飞行状态进行对比,证明了多级迭代优化策略的有效性和高效性,该策略在实际工程应用中取得了良好效果。     

飞机纵向飞行轨迹的优化与实现*

本文研究了飞机纵向飞行轨迹的优化技术,选用质点运动能量状态方程为飞机运动模型,直接操作成本为优化指标函数;飞机纵向飞行剖面被假定分为三个飞行段:爬升、巡航和下降;将能量状态引入指标函数,使其成为哈密顿函数中的独立变量,则由动态变分法和极小值原理得到对各飞行轨迹段的优化算法;尔后用Fibonacci单参数搜索法来予以实现。文中给出了部分仿真结果。     

基于双模型直接配置法的航天器轨迹优化

针对有限推力航天器轨迹优化问题,提出一种HLDL双模型直接配置法将航天器的飞行轨迹划分为最大推力弧段和零推力弧段.在两种弧段上分别采用了两种不同的建模方法并利用埃尔米特插值法将最优化问题转化为非线性规划问题(NLP).给出了节点和配置点数目的选取与所在弧段的平均曲率大小成正比的法则,解决用于有限推力航天器轨迹优化所涉及的关键问题.仿真结果表明提出的方法能有效的解决飞行器轨迹优化问题并具备很强的鲁棒性.     

基于遗传算法的飞机垂直剖面优化研究

垂直剖面优化的主要功能是优化飞机在纵向飞行过程中的航迹参数,是飞行计划及飞机性能管理的重要组成部分。垂直剖面优化的主要作用为减少飞机飞行过程中的燃油成本或综合考虑时间成本及燃油成本来降低飞行的运营成本。以某型飞机为研究对象,进行了垂直剖面性能数据分析,基于能量状态法完成了优化指标设计,采用遗传算法完成了纵向飞行轨迹优化求解,实现了最低燃油消耗、最小运营成本设计。     

高超声速飞行器机体推力耦合分析与协调控制方法研究

针对某型高超声速飞行器纵向巡航段模型对高度和速度的机动控制问题,研究并比较了采用吸气式超燃冲压发动机与火箭发动机作动力的飞行控制方法上的不同;重点分析了机体-推力耦合特性、高度-速度耦合特性以及超燃冲压发动机工作状态对飞行姿态的巨大影响;提出了油门和升降舵的协调控制方法,并进行了线性二次型控制律设计．通过仿真验证了该设计方法的有效性．     

基于形状法和伪谱法的小推力借力优化研究

小推力借力飞行轨道优化是一个多变量多约束的非线性优化问题,根据形状法和伪谱法,提出一种混合优化策略,分为全局优化和局部优化两个阶段进行。在全局优化阶段采用LT-PGA模型,即通过求解形状法小推力Lambert问题,搜索满足约束条件的小推力发射窗口,得到发射、借力和到达时间点。在局部优化阶段采用伪谱法得到推力控制率,用连接点设置解决借力行星处状态量的不连续问题。数值仿真结果表明,改进方法不用事先指定推力开关机序列,优化效率高,为初始设计阶段小推力借力飞行的轨道优化问题提供有益参考。     

Position control of a tail-sitter UAV using successive linearization based model predictive control

A successive linearization based model predictive control (SLMPC) method is proposed to control a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hovering flight. The dynamic model of the vehicle is derived, including a low-fidelity aerodynamic model and a propulsion system model. The position controller is developed by a state–space prediction model augmented with estimated disturbance and feedback integration terms. The time-varying weight in the objective function is included and the velocity of vehicle is considered as reference to improve the performance. The system is first tested in a software-in-loop environment followed by the real-time indoor flight tests. The results demonstrate the vehicle can precisely follow a trajectory and stably hold position under unsteady wind disturbance     

基于滚动速度障碍法的无人机山地航测避障路径规划研究

无人机在进行山地航测时,经常遭遇鸟类等动态障碍,若不能及时规避掉障碍,极容易发生坠机事故。为此,研究一种基于滚动速度障碍法的无人机山地航测避障路径规划方法。基于山地环境模型,结合飞行路径长度、路径平滑度建立一个综合目标函数并利用改进布谷鸟搜索算法求解,得到无人机山地航测的初始路径。对图像进行预处理后,识别无人机初始路径飞行过程中遇到的障碍物,并通过超声波测量无人机与障碍物之间的距离,以此建立速度障碍模型,实现速度障碍碰撞分析,通过滚动窗口的方式确定无人机与障碍物是否存在飞行冲突。基于滚动速度障碍避障方法实现滚动角度避障和速度避障,获取最终的优化路径,完成基于滚动速度障碍法的无人机山地航测避障路径规划。测试结果表明:航测避障路径长度为571.45m,平滑度为165.52,规划的方案更具合理性。     

Fuel consumption reduction effect of pre-acceleration before gliding of a vehicle with free-wheeling

Advanced fuel economy strategies are expected to reduce the fuel consumption of vehicles. An internal combustion engine (ICE) driving vehicle equipped with free-wheeling turns off the fuel injection and decouples the engine from the drivetrain when the driving force is not required. This paper proposes a method to reduce the fuel consumption of a vehicle equipped with free-wheeling. First, an optimization problem is formulated to minimize the fuel consumption of a vehicle with freewheeling when the traveling distance, the initial and final speed are specified and the vehicle needs to glide before arriving at the end point for fuel economy. The speed profile of the vehicle, engine operating point, and engine on/off timing are obtained as the results of the optimization. The analytical and numerical analyses results demonstrate the effectiveness and the fuel-saving mechanism of the obtained speed profile. The main finding of the analyses is that rather than starting a gliding stage immediately after an acceleration or a constant speed stage, adding a pre-acceleration stage before the gliding stage is more fuel-economic under some conditions independent of the complexity of the vehicle model. The obtained speed profile including a pre-acceleration stage is applied to a driving scenario including traffic congestions. The results demonstrate the effectiveness of the pre-acceleration stage in reducing fuel consumption for a vehicle equipped with free-wheeling.     

Integrated Guidance and Feedback Control of Underactuated Robotics System in SE(3)

An integrated guidance and feedback control scheme for steering an underactuated vehicle through desired waypoints in three-dimensional space, is developed here. The underactuated vehicle is modeled as a rigid body with four control inputs. These control inputs actuate the three degrees of freedom of rotational motion and one degree of freedom of translational motion in a vehicle body-fixed coordinate frame. This actuation model is appropriate for a wide range of underactuated vehicles including spacecraft with internal attitude actuators, vertical take-off and landing (VTOL) aircraft, fixed-wing multirotor unmanned aerial vehicles (UAVs), maneuverable robotic vehicles, etc. The guidance problem is developed on the special Euclidean group of rigid body motions, SE(3), in the framework ofgeometric mechanics, which represents the vehicle dynamics globally on this configuration manifold. The integrated guidance and control algorithm selects the desired trajectory for the translational motion that passes through the given waypoints, and the desired trajectory for the attitude based on the desired thrust direction to achieve the translational motion trajectory. A feedback control law is then obtained to steer the underactuated vehicle towards the desired trajectories in translation and rotation. This integrated guidance and control scheme takes into account known bounds on control inputs and generates a trajectory that is continuous and at least twice differentiable, which can be implemented with continuous and bounded control inputs. The integrated guidance and feedback control scheme is applied to an underactuated quadcopter UAV to autonomously generate a trajectory through a series of given waypoints in SE(3) and track the desired trajectory in finite time. The overall stability analysis of the feedback system is addressed. Discrete time models for the dynamics and control schemes of the UAV are obtained in the form of Lie group variational integrators using the discrete Lagrange-d’Alembert principle. Almost global asymptotic stability of the feedback system over its state space is shown analytically and verified through numerical simulations.     

低空无人机航空摄影高度自动测量方法研究

为控制低空无人机摄影高度,获得更加清晰的地理信息图像,需要对低空无人机摄影高度自动测量方法进行优化研究;当前方法主要利用射影几何知识的自动化标定方法实现低空无人机航空摄影高度的自动测量;该方法存在噪声影响严重,且测量误差较大的问题;为此,提出一种基于多传感器与卡尔曼滤波相结合的低空无人机航空摄影高度自动测量方法;该方法首先通过分析气压测量法计算各种气压因素对低空无人机航空摄影高度的影响,然后推导出大气对流层内气压随低空无人机航空摄影高度的变化;然后采用双GPS系统同时工作,对GPS、气压高度计和IMU测量获得的低空无人机航空摄影高度信号进行冗余备份;采用基于二阶多项式的修正方法对低空无人机航空摄影传感器输出值进行补偿和修正;根据动力学方程建立低空无人机航空摄影的动力学方程获得高度测量状态方程;最后采用卡尔曼滤波的线性最小方差估计准则对低空无人机航空摄影高度进行均方差估计计算,实现低空高度自动测量与校正。实验结果表明,所提方法具有精度高、收敛性好且滤波效果理想的优势。     

Two-Step System Identification and Trajectory Tracking Control of a Small Fixed-Wing UAV

An approach for obtaining dynamically feasible reference trajectories and feedback controllers for a small unmanned aerial vehicle (UAV) based on an aerodynamic model derived from flight tests is presented. The modeling method utilizes stepwise multiple regression to determine relevant explanatory terms for the aerodynamic coefficients. A dynamically feasible trajectory is then obtained through the solution of an optimal control problem using pseudospectral optimal control software. Discrete-time feedback controllers are further designed to regulate the vehicle along the desired reference trajectory. Simulations in a realistic operational environment as well as flight testing of the feedback controllers on the aircraft platform demonstrate the capabilities of the approach.     

On the Generation of Trajectories for Multiple UAVs in Environments with Obstacles

This paper presents a methodology based on a variation of the Rapidly-exploring Random Trees (RRTs) that generates feasible trajectories for a team of autonomous aerial vehicles with holonomic constraints in environments with obstacles. Our approach uses Pythagorean Hodograph (PH) curves to connect vertices of the tree, which makes it possible to generate paths for which the main kinematic constraints of the vehicle are not violated. These paths are converted into trajectories based on feasible speed profiles of the robot. The smoothness of the acceleration profile of the vehicle is indirectly guaranteed between two vertices of the RRT tree. The proposed algorithm provides fast convergence to the final trajectory. We still utilize the properties of the RRT to avoid collisions with static, environment bound obstacles and dynamic obstacles, such as other vehicles in the multi-vehicle planning scenario. We show results for a set of small unmanned aerial vehicles in environments with different configurations.     

推力矢量无人机尾坐式垂直起降控制

本文研究推力矢量无人机尾坐式垂直起降的控制方法.为解决欧拉角奇异的问题,提出了水平/垂直欧拉角综合姿态解算方法.为了获得快速响应又防止超调,控制器采用线性/恒加速度逼近和角速率限幅积分逼近控制方法,并且在最终输出舵偏时进行了反扭矩补偿.此外,本文提出了一种特殊的数据融合算法,该算法通过迭代计算保证了高度数据的准确性.由于尾坐式起降时机体姿态和高度具有强耦合关系,本文设计了一种基于滤波前馈加速度算法的高度控制器.尾坐式起降试验结果验证了本文所述控制方法的有效性.     

基于知识库的无人机作战自主决策方法的研究

提高无人机的自主决策能力是提升无人机在现代战争中作战能力的重要手段。通过对无人机对地作战过程的研究,分析归纳影响无人机自主决策的相关因素,并将无法用数学模型描述的军事规则使用产生式规则来表达,建立作战规则库。然后提出一种基于知识库的自主决策方法,该方法通过动态贝叶斯网络模拟人对态势的认知,通过产生式规则进行决策,其中加入实体的状态描述来控制决策流程,以此来完成无人机的自主决策。仿真结果表明,该方法科学有效,可使无人机自主做出合理决策。     

Spincopter Wing Design and Flight Control

This paper presents dynamical properties of an unmanned aerial vehicle (UAV), called spincopter. The vehicle structure is based on two wings that are forced in rotation (spinning) by propulsion system formed of two propellers. Based on devised dynamical model, that reveals inherent stability of the vehicle, composition of control algorithms for vertical and horizontal movement is proposed. Due to the specific configuration of the propulsion system, movement in horizontal direction is produced by pulsations in rotational speed of propulsion motors. An analysis of influence that such a configuration has on the vehicle dynamics is given. Finally, design recommendations for rotational wings are elaborated, based on extensive simulations of spincopter by using X-Plane® software package.