基于有限时间理论的临近空间拦截器末制导律PWPF调节器研究

针对拦截临近空间高速机动目标,基于有限时间理论,设计了有限时间收敛末制导律和脉冲宽度脉冲频率（PWPF）调节器。首先,介绍了加入PWPF调节器的末制导数学模型及工作原理;其次,设计了有限时间收敛制导律,应用有限时间理论证明了收敛条件和性质,并推广到推力受限条件下;最后,考虑视线（LOS）角速率快速收敛和发动机最小工作时间要求,设计了PWPF调节器参数。仿真结果表明,视线角速率在制导结束前的有限时间收敛至零,对目标机动具有鲁棒性,具有较高的制导精度,避免了发动机频繁开启,节省了燃料。     

Relevant experience learning: A deep reinforcement learning method for UAV autonomous motion planning in complex unknown environments

Unmanned Aerial Vehicles (UAVs) play a vital role in military warfare. In a variety of battlefield mission scenarios, UAVs are required to safely fly to designated locations without human intervention. Therefore, finding a suitable method to solve the UAV Autonomous Motion Planning (AMP) problem can improve the success rate of UAV missions to a certain extent. In recent years, many studies have used Deep Reinforcement Learning (DRL) methods to address the AMP problem and have achieved good results. From the perspective of sampling, this paper designs a sampling method with double-screening, combines it with the Deep Deterministic Policy Gradient (DDPG) algorithm, and proposes the Relevant Experience Learning-DDPG (REL-DDPG) algorithm. The REL-DDPG algorithm uses a Prioritized Experience Replay (PER) mechanism to break the correlation of continuous experiences in the experience pool, finds the experiences most similar to the current state to learn according to the theory in human education, and expands the influence of the learning process on action selection at the current state. All experiments are applied in a complex unknown simulation environment constructed based on the parameters of a real UAV. The training experiments show that REL-DDPG improves the convergence speed and the convergence result compared to the state-of-the-art DDPG algorithm, while the testing experiments show the applicability of the algorithm and investigate the performance under different parameter conditions.     

Inertial parameter estimation and control of non-cooperative target with unilateral contact constraint

In this paper, the relative sliding motion between the target and the manipulator’s end-effector is considered and characterized as a unilateral contact constraint. A new possible solution is presented to estimate the inertial parameters of a non-cooperative target while the relative sliding motion exists. First, the detailed analysis of the dynamical model is presented, and a parameter-explicit linear time-varying model is obtained. Then, an extended state observer is constructed based on the new model, which can effectively estimate the unknown inertial parameters of the target when relative sliding motion exists. As the modified reactionless controller requires the knowledge of inertial parameters, a hybrid post-capture control scheme is also established based on the switch law between different controllers. The correctness and efficiency of the proposed algorithm are validated by numerical simulation, which proves a potential framework for the non-cooperative target post-capture operation.     

一种常用两次扫描算法的改进

针对交会对接最后逼近段光学成像敏感器图像处理中的快速连通域标记问题,将标记融合和两次扫描相结合,改进了连通域标记中常用的两次扫描算法,并基于标志灯成像的几何约束和统计约束给出了可完成目标粗识别的连通域标记算法.仿真结果表明这两种改进措施都可提高有效连通域标记的效率.改进后的连通域标记算法处理一幅1 024×1 024的图像,其50次重复运行的平均耗时小于98 ms,具备实时应用的能力.     

柔性机械臂辅助空间站舱段对接阻抗控制

空间机械臂辅助舱段对接过程中存在测量与控制误差,易导致对接机构间存在较大接触力,传统FMA (Force MomentAccommodation)控制方法在测量接触力时无法消除大负载惯性力对测量的影响,且测量仪器的引入会进一步降低空间柔性机械臂的刚度。为此,文章提出了柔性机械臂辅助大负载空间舱段对接的阻抗控制方法,采用拉格朗日法推导了空间机械臂的关节输入力矩方程作为前馈输入,建立了含动力学前馈的空间机械臂阻抗控制程序,并以在商业软件ADAMS中建立的空间柔性机械臂与对接舱段组成的系统动力学模型作为控制对象,对系统进行ADAMS灢Matlab联合仿真。仿真结果表明,按照此控制方法,系统可克服外力干扰使目标解析点按照期望的方式运动;同时,通过测量机械臂关节运动参数即可实现对外力的准确感知,而不需额外添加力传感器,既消除了大负载惯性力对测量的影响,也不会导致柔性机械臂刚度的降低。     

昆虫翅膀图像特征的亚像素级提取方法

昆虫翅脉、翅脉交点及翅膀边缘是昆虫翅膀运动变形三维重构的主要依据.通过分析这三种特征的图像特点,对于翅脉中心,采用Hessian矩阵求出灰度极值点方向,并用二次曲线拟合该方向的灰度变化,通过确定该曲线极值点位置来提取亚象素翅脉中心;然后通过求灰度图像的梯度,在其梯度变化方向求极值点的方法提取翅膀边缘特征;此外根据翅脉方向变化的连续性提出了邻域角度约束方法确定翅脉交叉点,从而最终提取到亚像素级的翅膀边缘、翅脉及交叉点等特征.实际应用证明该方法是较为有效的.     

费用约束下含应力优化的CSADT设计

恒定应力加速退化试验(CSADT,Constant Stress Accelerated Degradation Testing)方案中需要确定的变量有应力水平、各应力下样本量、监测间隔和各应力下监测次数.如何对CSADT的应力水平进行优化目前很少有人探讨.针对这一问题提出一种在费用约束下将上述4个变量进行综合优化的方法.首先用随机过程描述CSADT下产品的性能退化过程,然后以产品在使用条件下p分位寿命可靠度的渐近方差最小为目标,以试验费用不超过预算为约束条件,给出CSADT的4个优化变量,并给出应用该优化方法的仿真算例.最后,优化方案对模型参数偏差的敏感性分析表明,在一定偏差范围内优化结果具有良好的稳健性.