Motion prediction of a non-cooperative space target

Capturing a non-cooperative space target is a tremendously challenging research topic. Effective acquisition of motion information of the space target is the premise to realize target capture. In this paper, motion prediction of a free-floating non-cooperative target in space is studied and a motion prediction algorithm is proposed. In order to predict the motion of the free-floating non-cooperative target, dynamic parameters of the target must be firstly identified (estimated), such as inertia, angular momentum and kinetic energy and so on; then the predicted motion of the target can be acquired by substituting these identified parameters into the Euler’s equations of the target. Accurate prediction needs precise identification. This paper presents an effective method to identify these dynamic parameters of a free-floating non-cooperative target. This method is based on two steps, (1) the rough estimation of the parameters is computed using the motion observation data to the target, and (2) the best estimation of the parameters is found by an optimization method. In the optimization problem, the objective function is based on the difference between the observed and the predicted motion, and the interior-point method (IPM) is chosen as the optimization algorithm, which starts at the rough estimate obtained in the first step and finds a global minimum to the objective function with the guidance of objective function’s gradient. So the speed of IPM searching for the global minimum is fast, and an accurate identification can be obtained in time. The numerical results show that the proposed motion prediction algorithm is able to predict the motion of the target.     

NOx emissions of turbofan powered unmanned aerial vehicle for complete flight cycle

Unmanned Aerial Vehicles (UAVs) have been getting more and more popular in both civil and military arena. Similar to manned aircraft, their propulsion systems or engines emit harmful gases such as nitrogen oxides. Since UAVs have different mission profiles and operational parameters than manned aircraft, it is worthy to investigate their NO_x emissions. Therefore, in this study, NO_x emissions of a turbofan powered UAV for complete flight cycle was calculated and optimized within a range of altitude and speed parameters. NO_x emissions were calculated based on ICAO ground test data and corrected to any speed and altitude during flight legs using both Boeing Fuel Flow Method 2 and DLR Fuel Flow Method. Total NO_x emissions were calculated for complete flight cycles for different altitude and speed parameters. Numerical results were presented graphically and additionally optimization studies were conducted. Optimization studies include determination and comparison of speed and altitude for minimum NO_x emissions by the two fuel flow methods and maximum loiter time achievable by UAV.     

Multi-UAV coordination control by chaotic grey wolf optimization based distributed MPC with event-triggered strategy

The paper proposes a new swarm intelligence-based distributed Model Predictive Control (MPC) approach for coordination control of multiple Unmanned Aerial Vehicles (UAVs). First, a distributed MPC framework is designed and each member only shares the information with neighbors. The Chaotic Grey Wolf Optimization (CGWO) method is developed on the basis of chaotic initialization and chaotic search to solve the local Finite Horizon Optimal Control Problem (FHOCP). Then, the distributed cost function is designed and integrated into each FHOCP to achieve multi-UAV formation control and trajectory tracking with no-fly zone constraint. Further, an event-triggered strategy is proposed to reduce the computational burden for the distributed MPC approach, which considers the predicted state errors and the convergence of cost function. Simulation results show that the CGWO-based distributed MPC approach is more computationally efficient to achieve multi-UAV coordination control than traditional method.     

A parameterized geometry design method for inward turning inlet compatible waverider

Intensive studies have been carried out on generations of waverider geometry and hypersonic inlet geometry. However, integration efforts of waverider and related air-intake system are restricted majorly around the X43A-like or conical flow field induced configuration, which adopts mainly the two-dimensional air-breathing technology and limits the judicious visions of developing new aerodynamic profiles for hypersonic designers. A novel design approach for integrating the inward turning inlet with the traditional parameterized waverider is proposed. The proposed method is an alternative means to produce a compatible configuration by linking the off-the-shelf results on both traditional waverider techniques and inward turning inlet techniques. A series of geometry generations and optimization solutions is proposed to enhance the lift-to-drag ratio. A quantitative but efficient aerodynamic performance evaluation approach （the hypersonic flow panel method） with lower computational cost is employed to play the role of objective function for opti- mization purpose. The produced geometry compatibility with a computational fluid dynamics （CFD） solver is also verified for detailed flow field investigation. Optimization results and other numerical validations are obtained for the feasibility demonstration of the proposed method.     

多值逻辑函数最小化的McCluskey—Quine方法改进及程序实现

多值逻辑电路的发展，使得以往的化简方式已不能适应电路取值的增高和函数项的增加。本文以三变量三值函数为例，讨论了多值逻辑电路化简的物理背景，采用改进的McCluskey-Quine方法进行最小化的算法，以及质蕴含项覆盖问题的求解，并给出了程序流程。由于该程序采用的面向对象技术，经过适当扩展可以应用于多变量多值函数。     

Period selection for integrated controller tasks in cyber-physical systems

Performance optimization of cyber-physical systems(CPS)calls for co-design strategies that handle the issues in both computing domain and physical domain.Periods of controller tasks integrated into a uniprocessor system are related to both control performance and real-time schedulability analysis simultaneously.System performance improvement can be achieved by optimizing the periods of controller tasks.This paper extends an existing model to select task periods in real-time for CPS with fixed priority controller tasks scheduled by rate-monotonic algorithm.When all the tasks can be integrated,the analytic solution of the problem is derived by using the method of Lagrange multipliers and gradient descent method is evaluated to be suitable online.To further deal with the condition that the system is overloaded,an integrated method is proposed to select periods of tasks online by selecting a subset of tasks first and then optimizing the periods for them.Experimental results demonstrate that our method yields near-optimal result with a short running time.     

低速颤振模型的动力学特性设计

飞机在打样设计阶段除了需要满足结构强度和刚度要求外 ,还必须满足颤振稳定性要求。根据相似理论 ,并利用结构优化设计方法 ,对某机翼低速颤振吹风模型的动力特性 (模型的一阶弯曲、一阶扭转和二阶弯曲频率 )进行了设计。此方法改变了仅凭经验反复试凑的设计调参方法 ,提高了模型设计的效率 ,缩短了设计周期 ,具有良好的工程应用前景。     

二维高超声速压缩面斜激波系的优化配置

选择进气道外压缩段的气流转折角为设计变量,以进气道的压升比为约束条件,分别以总压恢复系数和阻力系数为优化目标,基于一维气体动力学,在飞行马赫数6,飞行高度25 km,进气道出口气流方向与自由来流夹角等于0,°2,°4°和6°的条件下,对二维混压式高超声速进气道进行了优化设计,得到了优化的斜激波配置。优化结果表明,在所讨论的各种情况下,以阻力系数最小为目标得到的外压缩段斜激波系与以总压恢复系数最大为目标得到的外压缩段斜激波系基本相同,都近似为等强度斜激波系。运用数值模拟手段验证了等强度斜激波系配置原则,本文提供的方法可以用于二维混压式高超声速进气道的初步设计。     

固体火箭发动机稳态燃速二维模型参数最优化辨识

1引言发动机参数辨识常用方法是最小二乘法[1],即将参数估计问题转化为多元函数求极值问题,通过迭代选择待估参数值,使燃烧室压强计算值和实验值的残差平方和最小。采用最小二乘法进行参数辨识存在局限性[2],需要通过台劳级数展开式近似模型替代真实数学模型计算残差平方和对待     

飞/推综合控制模式亚声速半物理仿真试验

飞/推综合控制考虑飞机和发动机之间的性能耦合，彼此进行信息的综合，从整体最优的设计出发，充分发挥飞机和发动机的性能潜力，提高飞机性能。为了验证飞/推综合控制模式的性能效益，提出并开展了该控制模式在亚音速下的半物理仿真试验的研究，结果表明：在平飞加速工况下，采用最大推力模式，可提高发动机推力约9％；在亚音速巡航时，采用最小油耗模式，可节省单位油耗约1．5％。