格的微分

在偏序关系的基础上给出了格的微分定义,同时也给出了恒等微分和保序微分的定义。通过格微分的弱正则性和正则性,研究格的微分的一些性质。     

多架无人作战飞机攻击行为的协调

建立了基于Agent的无人作战飞机指挥控制系统的形式化语义模型，提出了无人作战飞机编队的联合作战目标、联合作战意图和协同攻击效能的定义，以及结合联合作战意图、协同作战效能的多架无人作战飞机编队攻击行为的协调方法。仿真结果表明，结合联合作战意图和协同攻击效能的攻击行为可有效地提高编队的作战效能。     

螺纹联接结构密封材料应用研究

提出了一种适用于固体火箭发动机（SRM）的新型密封结构，并对应用于特定尺寸的螺纹联接结构方式、胶种选择进行了研究。通过压力、高低温循环等大量的试验和理论分析表明：采用填充密封胶的螺纹联接密封结构具有优异的密封性，适宜在固体火箭发动机环境中应用。     

基于鲁棒故障观测器的非线性离散系统容错控制设计

针对存在执行器故障以及未知干扰的非线性离散系统,提出了一种鲁棒故障估计与容错控制方法。首先在未知系统干扰作用下,设计鲁棒故障观测器实现系统状态和执行器故障的同步估计;然后根据鲁棒故障观测器得到的系统状态估计和故障估计信息设计容错控制器,进行状态反馈容错控制,同时基于D稳定与H_∞控制理论对鲁棒故障观测器和容错控制器进行设计,实现了多约束条件下的故障估计与容错控制;最后用飞行控制系统模型验证了所提方法的有效性。     

用最优估计法从飞行试验数据估计飞机迎角及测量误差

本文采用最优估计方法——信息平方根滤波和平滑算法,利用飞行数据对J-7原型机安装的92/BJ311型风标式迎角传感器的迎角测量误差进行了估计,给出了飞行迎角的校准公式。状态估计系统方程采用六自由度非线性方程。飞行动作采用推拉机动方法.飞行试验结果与风洞值进行了比较分析,证明飞行试验获得的误差修正系数和零偏误差是合理的。     

等维灰数递补动态预测在机场客运量预测中的应用

基于灰色系统等维灰数递补动态预测和残差GM（1，1）修正模型，对其应用的可行性进行了有益的探讨，并结合实例，对首都国际机场中短期客运量进行了预测。通过调整原始样本中的变异数据，得到比较理想的预测结果．经检验预测结果是可信的。该研究为机场客运量预测提供了一种方法，可供借鉴。     

A novel two-stage extended Kalman filter algorithm for reaction flywheels fault estimation

This paper investigates the problem of two-stage extended Kalman filter(TSEKF)-based fault estimation for reaction flywheels in satellite attitude control systems(ACSs). Firstly, based on the separate-bias principle, a satellite ACSs with actuator fault is transformed into an augmented nonlinear discrete stochastic model; then, a novel TSEKF is suggested such that it can simultaneously estimate satellite attitude information and actuator faults no matter they are additive or multiplicative; finally, the proposed approach is respectively applied to estimating bias faults and loss of effectiveness for reaction flywheels in satellite ACSs, and simulation results demonstrate the effectiveness of the proposed fault estimation approach.     

Distributed formation control of multiple aerial vehicles based on guidance route

Formation control of fixed-wing aerial vehicles is an important yet rarely addressed problem because of their complex dynamics and various motion constraints, such as nonholonomic and velocity constraints. The guidance-route-based strategy has been demonstrated to be applicable to fixed-wing aircraft. However, it requires a global coordinator and there exists control lag, due to its own natures. For this reason, this paper presents a fully distributed guidance-route-based formation approach to address the aforementioned issues. First, a hop-count scheme is introduced to achieve distributed implementation, in which each aircraft chooses a neighbor with the minimum hop-count as a reference to generate its guidance route using only local information. Next, the model predictive control algorithm is employed to eliminate the control lag and achieve precise formation shape control. In addition, the stall protection and collision avoidance are also considered. Finally, three numerical simulations demonstrate that our proposed approach can implement precise formation shape control of fixed-wing aircraft in a fully distributed manner.     

Cubature Kalman filter with closed-loop covariance feedback control for integrated INS/GNSS navigation

Cubature Kalman Filter (CKF) offers a promising solution to handle the data fusion of integrated nonlinear INS/GNSS (Inertial Navigation System/Global Navigation Satellite System) navigation. However, its accuracy is degraded by inaccurate kinematic noise statistics which originate from disturbances of system dynamics. This paper develops a method of closed-loop feedback covariance control to address the above problem of CKF. In this method, the posterior state and its covariance are fed back to the filtering process to constitute a closed-loop structure for CKF covariance propagation. Subsequently, based on the maximum likelihood principle, a control scheme of the prior state covariance is established by using the feedback state and covariance within an estimation window and further adopting a proportional coefficient to amplify the feedback terms in recent time steps for the full use of new information to reflect actual system characteristics. Since it does not directly use kinematic noise covariance, the proposed method can effectively avoid the adverse impact of inaccurate kinematic noise statistics on filtering solutions. Further, it can also guarantee the prior state covariance to be positive semi-definite without involving extra measures. The efficacy of the proposed method is validated by simulations and experiments for integrated INS/GNSS navigation.     

A practical filter error method for aerodynamic parameter estimation of aircraft in turbulence

It is common for aircraft to encounter atmospheric turbulence in flight tests. Turbulence is usually modeled as stochastic process noise in the flight dynamics equations. In this paper, parameter estimation of nonlinear dynamic system with both process and measurement noise was studied, and a practical filter error method was proposed. The linearized Kalman filter of first-order approximation was used for state estimation, in which the filter gain, along with the system parameters and the initial states, constituted the parameter vector to be estimated. The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method, and the sensitivities of observations to unknown parameters were calculated by finite difference approximation. Some practical aspects of the method application were discussed. The proposed filter error method was validated by the flight simulation data of a research aircraft. Then, the method was applied to the flight tests of a subscale aircraft, and the aerodynamic stability and control derivatives were estimated. All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach. It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.