一种针对运动目标的飞行器航迹搜索算法

鉴于目前大部份的航迹规划方法研究都局限于静止目标，提出了一种针对运动目标的飞行器航迹规划方法。该算法借鉴自学习实时A*搜索的思想，将飞行器的运动与航迹搜索结合在一起，可以对目标的每一步移动实时作出反映。通过在限定的时间内扩大寻优范围，该算法不但可以满足实时在线应用的要求，而且可以有效地避免不可行区域，并使生成的航迹更加优化。实验结果表明，本文算法能有效地处理各种航迹约束，实时地生成满意的三维航迹。     

基于模糊自适应卡尔曼滤波的INS/GPS 组合导航系统算法研究

针对车载组合导航系统量测噪声统计特性随实际工作条件的不同而变化的特点,提出了一种基于模糊自适应卡尔曼滤波的车载INS/GPS组合导航算法。该方法通过监视理论残差与实际残差的比值是否在一附近,应用模糊推理系统不断的调整量测噪声协方差阵的加权,对卡尔曼滤波的量测噪声协方差阵进行递推在线修正,使其逐渐逼近真实噪声水平,从而使滤波器执行最优估计,提高导航系统的精度。对车载组合导航系统的仿真结果表明,这种算法对时变的量测噪声具有较强的自适应性,进而精度比常规卡尔曼滤波也大为提高,是一种可行的车载组合导航算法。     

有控飞行力学在无人飞行器研制和使用中的作用

本文从工程实践观点出发，结合无人飞行器，特别是战术导弹和制导兵器的特点，扼要讨论了与此密切相关的有控习行力学研究工作的某些进展情况，文中将有控习行力学问题分为两大类，即典型的飞行力学问题和相关的飞行力学问题，强调了多学科交 对飞行力学研究的重要意义；同时，还指出了有控飞行力学在未来軎与研制和使用中的作用。     

主导极点圆域约束下具L_2有界不确定性系统的鲁棒优化设计问题

根据闭环极点的渐近性质，在考虑了L2有界不确定性对系统闭环极点的最坏影响下利用复s平面与复ω平面之间的Mobins变换，给出满足闭环主导极点圆域约束的状态加权阵Q的选取过程，实现保证一定稳定格度并具有主导极点与非主导极点分布的鲁棒性优化设计。仿真算例表明了设计的有效性。     

虚拟高频采样控制方案及在姿控系统中的应用

提出了一种新的控制方案,即虚拟高频采样控制方案,对其进行了详细的理论分析,并在此方案基础上应用离散域设计方法完成了某飞行器的稳定性分析,进行了半实物仿真试验,结果表明,系统有足够的稳定裕度,各项性能指标满足设计要求.     

提高控制系统可靠性惯性仪表冗余方案分析

叙述了提高控制系统可靠性惯性仪表冗余的几种典型方案，对它们的优缺点进行了分析、比较。最后，提出冗余的一般准则和注意事项。     

无动力自动着陆轨道的鲁棒性分析

文中定义了能量梯度的概念,作为评价能量积累和消耗能力的指标。针对跨大气层飞行器对象特性的特点,重点讨论了气动参数的不确定性存在时的着陆点性能、整个下滑轨道容许的气动参数的不确定性范围和对初始动压的抑制能力,结果表明下滑轨道具有较好的鲁棒性。     

Cascade-type guidance law design for multiple-UAV formation keeping

A procedure to compute guidance commands for controlling the relative geometry of multiple unmanned aerial vehicles (UAVs) in formation flight is proposed. The concepts of branch, global leader, and local leader/follower are used to represent the whole formation geometry. A positive-definite function defined in terms of the formation error is then introduced and the Lyapunov stability theorem is used to obtain the cascade type guidance law. This scheme leads to the synchronized flight of all UAVs while maintaining formation geometry. The results of a high fidelity nonlinear simulation of a reconnaissance and surveillance mission example are presented to show the effectiveness of the proposed guidance law.     

Aircraft robust multidisciplinary design optimization methodology based on fuzzy preference function

This paper presents a Fuzzy Preference Function-based Robust Multidisciplinary Design Optimization (FPF-RMDO) methodology. This method is an effective approach to multidisciplinary systems, which can be used to designer experiences during the design optimization process by fuzzy preference functions. In this study, two optimizations are done for Predator MQ-1 Unmanned Aerial Vehicle (UAV): (A) deterministic optimization and (B) robust optimization. In both problems, minimization of takeoff weight and drag is considered as objective functions, which have been optimized using Non-dominated Sorting Genetic Algorithm (NSGA). In the robust design optimization, cruise altitude and velocity are considered as uncertainties that are modeled by the Monte Carlo Simulation (MCS) method. Aerodynamics, stability and control, mass properties, performance, and center of gravity are used for multidisciplinary analysis. Robust design optimization results show 46% and 42% robustness improvement for takeoff weight and cruise drag relative to optimal design respectively.     

Real-time trajectory planning for UCAV air-to-surface attack using inverse dynamics optimization method and receding horizon control

This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle (UCAV) performing autonomous air-to-surface (A/S) attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem (RHC-OCP). In particular, an approximate elliptic launch acceptable region (LAR) model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom (2-DOF) receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.