基于信息融合的航空发动机剩余寿命预测

利用航空发动机状态监测信息,考虑到信息本身具有的误差性和随机性等特点,采用贝叶斯线性模型融合了监测信息,实现了综合利用多源信息的进行航空发动机性能衰退评估;以性能衰退评估结果为输入变量,建立基于Gamma随机过程的可靠性评估模型,预测在指定性能可靠性水平下的剩余寿命.通过算例,分析了不同监测参数对剩余寿命预测的影响.该方法能将性能监测与可靠性分析集成到一个框架中,充分利用了多种状态监测信息,结果更加准确,更符合控制航空发动机维修决策风险的实际.      

基于严格成像模型的卫星姿态角系统误差补偿

为消除卫星在轨运动过程中俯仰、偏航、滚动对遥感影像地面定位的影响,建立了卫星姿态角系统误差补偿模型,即在严格成像模型的基础上,对姿态角进行直接调整,以减小定位误差。利用环境减灾-1B（HJ-1B）卫星CCD1相机遥感影像进行分析,在单景影像的定位中,借助于2个地面控制点,将其系统误差减小到原来的1/3,从而验证了模型的有效性,为进一步在轨检校相机内部静态参数提供了前提。     

基于混合灵敏度的航空发动机切换控制系统设计

针对航空发动机工作安全边界,提出了一种基于切换控制的航空发动机控制系统设计方法.给出了切换控制策略的设计思路及切换稳定性的条件.给出基于混合灵敏度的航空发动机多回路切换鲁棒控制器设计方法,并构造了线性矩阵不等式.通过基于计算得到的控制器参数仿真表明,采用该切换方式相比于Min/Max切换方式消除了积分饱和在切换中延迟影响,提高发动机的动态响应能力及鲁棒性,同时可以保证切换的稳定性.      

带输入饱和的直升机信息融合解耦控制算法

针对带输入饱和的直升机解耦控制问题,提出了一种改进的信息融合解耦控制算法,通过融合主通道和相应耦合通道期望输出和控制能量的软约束信息,以及系统状态方程和输出方程的硬约束信息,获得二次型性能指标下解耦控制律的最优估计,使直升机的内回路控制具有良好的动态特性和解耦性能。通过控制能量软约束信息的自适应调节,使求取的控制量满足输入饱和限制要求,避免了因输入饱和导致的解耦性能变差和驱动器过载问题。提出的信息融合控制算法基于被控对象的离散模型实现,容易应用于工程实际中。仿真结果表明了该算法的有效性。     

飞行器再入段最优自适应积分滑模姿态控制

针对飞行器再入段的姿态跟踪控制问题,提出了一种最优自适应积分滑模控制(Optimal Adaptive Integral Sliding Mode Control, OAISMC)方法。首先针对飞行器的标称模型设计了基于状态相依黎卡提方程(State Dependent Riccati Equation, SDRE)的姿态控制器,使标称系统的性能满足提出的最优指标。然后,考虑系统的不确定性和外部干扰,在SDRE标称控制器的基础上设计积分滑模姿态控制方法,使系统在满足性能指标要求的同时,对不确定性和干扰具有鲁棒性。进一步采用自适应方法调整切换增益,避免了对复合干扰上界的先验要求,并引入滑模干扰观测器提高系统的性能。最后,仿真结果表明,在考虑外部干扰以及气动系数和大气密度摄动的情况下,本文设计的控制方法不仅能够实现姿态跟踪、满足设计的性能指标,而且具有较好的鲁棒性。     

基于插值DFT的弹体弹性自适应陷波方法

针对现代导弹弹性频率低、频率不确定范围大,传统陷波方法会造成严重相位滞后的问题,提出一种基于插值离散傅立叶变换（IpDFT）的自适应陷波方法。该方法利用修正Jacobsen方法辨识、跟踪测量信号中弹性模态的频率,并调整陷波器的中心频率来实现自适应陷波。该估计器频率辨识精度接近克拉美罗下界（CRLB）,弹性幅值变化对辨识精度的影响很小。仿真对比表明,该方法灵敏度高、辨识快、相位延迟小、弹性抑制效果好。与固定参数陷波器相比,相位滞后从29.4°减小到11.86°;与一类用自适应陷波器频率辨识方法相比,辨识时间从2s减少到0.25s,弹性振动幅值峰值为其10%。     

带有柔性补偿的柔性关节空间机器人的增广自适应控制及关节振动抑制

The problems of joint motion control and flexible vibration suppression of a flexible joint space based robot for manipulating an unknown payload are studied. Based on the system linear momentum conservation and the Lagrange method, the under actuated dynamics model of the space robot is established. For convenience of the design of its control system, the system is divided into both fast and slow subsystems by using the joint flexibility compensation technique and the singular perturbation theory. A torque differential feedback controller is proposed for the fast subsystem to suppress the joints’ flexible vibration, meanwhile an adaptive control scheme based on the augmentation approach is designed for the slow subsystem to realize the joint trajectory asymptotic tracking under the condition of unknown payload parameters. Because of introduction of the flexibility compensation technique, the presented control scheme can equivalently increase the joint stiffness, and it is suitable to control the space robot systems with low joint stiffness. Moreover, the effect of unknown parameters is real time compensated by its adaptive controller, and then the specified joint motion task is achieved precisely. The effectiveness of the scheme is verified by the corresponding simulation results.     

不同重力环境下空间机械臂神经自适应鲁棒控制

针对空间机械臂从地面装调到空间应用过程中重力项的变化问题,提出了一种神经网络自适应鲁棒补偿控制策略用于空间机械臂的末端控制,从而实现在地面重力环境下装调好的空间机械臂在空间微重力环境下实现在轨操控任务。通过神经网络在线建模来逼近系统模型中变化的重力项,逼近误差及系统的不确定性通过自适应鲁棒控制器来补偿。该控制策略不依赖于系统的模型,避免了回归矩阵的复杂计算及未知参数的估计,降低了计算量。基于李亚普诺夫理论证明了闭环系统的渐近稳定性。仿真结果表明该控制器对不同重力环境下空间机械臂的末端控制均能达到较高的控制精度,具有重要的理论研究和工程应用价值。     

基于线性协方差的月球上升器主动段误差分析

提出一种线性协方差误差分析方法用于月球上升器主动段多种误差源影响分析.给出了动力上升段动力显式制导(PEG,powered explicit guidance)制导律线性化解析方法,得到了PEG 3个制导参数的线性化显式表达.在此基础上用于分析月球上升器主动段在存在初始状态偏差、参数不确定等情况下,终端时刻的高度偏差、速度大小偏差以及飞行路径角偏差.通过和蒙特卡洛的仿真对比,验证了上述线性化方法的有效性.     

Multiple air route crossing waypoints optimization via artificial potential field method

Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization, capacity and resilience in dealing with air traffic congestion and delay. However, research is lacking on the optimization of multiple Crossing Waypoints (CWPs) in the fragmented airspace separated by Prohibited, Restricted and Dangerous areas (PRDs). To tackle this issue, this paper proposes an Artificial Potential Field (APF) model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles. An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs, air route segments and PRDs. Based on the framework, an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost. The proposed model is applied to a busy controlled airspace. And the obtained results show that after optimization the safety-related indicators: conflict number and controller workload reduced by 7.75% and 6.51% respectively. As for the cost-effectiveness indicators: total route length, total air route cost and non-linear coefficient, declined by 1.74%, 3.13% and 1.70% respectively. While the predictability indicator, total flight delay, saw a notable reduction by 7.96%. The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.