空间站对日定向装置半物理试验台关键技术

为有效模拟空间站对日定向装置驱动性能受柔性太阳翼的扰动，验证对日定向装置驱动控制性能，采用半物理试验技术对对日定向装置进行地面试验考核。设计超高刚度及运动误差无附加力自适应的半物理试验台，对支撑连接机构和加载单元进行有限元分析与刚度测试；建立大尺度柔性太阳翼的动力学模型，并采用Wilson θ法进行动力学模型的实时数值求解；运用跟踪微分法对对日定向装置低速运行下的角速度和角加速度进行估计；最后通过对半物理试验台的响应精度、加载有效性进行仿真和试验考核，结果表明试验台加载力矩幅值为 0~ 85 Nm、频率为0.01~3 Hz时，绝对精度优于0.85 Nm，相对精度优于1%，从而验证了半物理试验台对太阳翼扰动载荷模拟的真实有效性，可实现对日定向装置的性能测试。     

三容实验系统的变结构PID控制

基于非线性系统的反馈线性化,介绍了一种变结构PID控制方法．该方法能够有效地改善有控制量约束系统的控制性能．以某试验系统为被控对象,在对其进行反馈线性化同时实现静态解耦的基础上,给出了变结构PID控制的实验结果,并与常规PID控制进行了比较．结果表明了变结构PID控制的优越性．     

一种纯距离跟踪滤波器的改进算法

针对纯距离目标跟踪可观测程度较低的问题,提出一种基于角度参数的纯距离目标跟踪改进算法。文中方法将系统的观测区间范围划分为若干个子扇区,每个子扇区采用一个独立的加权扩展卡尔曼滤波器进行纯距离跟踪,利用贝叶斯理论来修正各滤波器的权重,系统的输出为各并行运行的滤波器估计值的加权和,最终获得目标的运动轨迹。系统的仿真结果表明,方法收敛速度快,跟踪精度高于扩展卡尔曼滤波器的跟踪精度。     

目标机动时的一种非线性末制导律

本文研究了在空间拦截中导弹的脱靶量，并分析了影响脱靶量的因素。利用非线性精确线性化理论设计了目标机动时的非线性末制导律。     

计入带电粒子入射角度对次级电子效应影响时航天飞行器的带电特性

本文采用由实验得到的带电粒子入射角度对次级电子的影响关系,根据轨道限制电流收集理论,导出了不同几何形体航天器的次级电子数通量表达式;并按局部电流平衡模型,计算了航天器背阴面的带电电位。结果表明,计入带电粒子入射角的影响后,航天器表面负电位的数值有一定减少。因此,在计算航天器表面带电时,应当考虑这种影响。     

权值动态分配的加权平均法在姿态解算中的应用

鉴于各种姿态算法解算后的精度不高,提出将加权平均法应用于捷联惯导系统的姿态解算中.针对实际应用中无法准确获得姿态角度的真实值这一情况,提出对解算误差进行实时估计的方法,再基于最优权值分配的原则进行权值动态分配.对几种姿态解算算法进行了有效的融合,并应用到姿态解算模块的实际测量中.测量结果分析表明此种方法很大程度上减少了单一算法的解算误差及测量的误差,提高了测量的精度.     

基于反馈线性化的高速无人机自适应控制系统设计

高速无人机是典型的复杂非线性、参数不确定性系统,且各控制通道之间存在强耦合作用,这对飞行控制系统设计提出了严峻挑战。针对其非线性特性和耦合特性,采用精确反馈线性化理论将无人机动力学模型解耦为3个独立的子系统,即滚转、俯仰和偏航通道;应用模型参考自适应控制方法分别设计每个通道的姿态控制器。研究表明,上述线性化方法能够实现三通道解耦,所设计控制系统满足飞行控制性能要求,且对气动参数摄动和外部干扰具有较强的鲁棒性。     

吸气式组合动力高超声速飞行器上升段制导方法研究

针对涡轮/冲压/火箭三组合动力水平起降高超声速飞行器爬升段飞行轨迹设计和制导律设计问题，首先考虑宽速域组合动力发动机多模态特性和高低速气动特性差异，分别开展了涡轮段、引射段、纯冲压段及冲压火箭段的飞行策略研究，提出了不同阶段的飞行攻角剖面构型和火箭流量剖面构型，将无穷维轨迹优化问题转化为有限维参数规划问题，进而完成了组合动力上升段飞行轨迹的优化设计；在此基础上，结合轨迹线性化控制方法，开展了组合动力上升段轨迹跟踪制导律设计研究，给出了保证闭环稳定性和控制品质的制导律参数设计准则，最后通过开展仿真分析说明了提出轨迹设计及制导方法的有效性。     

Adaptive neural network control of nonlinear systems with unknown dynamics

In this study, an adaptive neural network control approach is proposed to achieve accurate and robust control of nonlinear systems with unknown dynamics, wherein the neural network is innovatively used to learn the inverse problem of system dynamics with guaranteed convergence. This study focuses on the following three contributions. First, the considered system is transformed into a multi-integrator system using an input–output linearization technique, and an extended state observation technique is used to identify the transformed states. Second, an iterative control learning algorithm is proposed to achieve the neural network training, and stability analysis is given to prove that the network’s predictions converge to ideal control inputs with guaranteed convergence. Third, an adaptive neural network controller is developed by combining the trained network and a proportional-integral controller, and the long-standing challenge of model-based methods for control determination of unknown dynamics is resolved. Simulation results of a virtual control mission and an aerospace altitude tracking mission are provided to substantiate the effectiveness of the proposed techniques and illustrate the adaptability and robustness of the proposed controller.     

Modeling and control of a novel electro-hydrostatic actuator with adaptive pump displacement

The variable pump displacement and variable motor speed electro-hydrostatic actuator (EHA), one of the three types of EHAs, has advantages such as short response time, flexible speed regulation, and high efficiency. However, the nonlinearity of its double-input single-output system poses a great challenge for system control. This study proposes a novel EHA with adaptive pump displacement and variable motor speed (EHA-APVM). A closed-loop position is realized using a servomotor. Moreover, the displacement varies with the system pressure; thus, the EHA-APVM is a single-input and single-output system. Firstly, the working principles of the EHA-APVM and the pump used in the system are introduced. Secondly, a nonlinear mathematical model of the proposed EHA-APVM control system is established, and a feedback back-stepping (FBBS) control algorithm is introduced to transform the complex nonlinear system into a linear system on the basis of the back-stepping control theory. Finally, simulation results prove that the EHA-APVM has a quick response and high robustness to variations of the load and the pump displacement. In this work, the size and weight of the motor are significantly reduced because the maximum power requirement is reduced, which is very beneficial for using the actuator in airborne equipment.