参数不确定空间机械臂关节轨迹跟踪的增广自适应控制方案

讨论了载体位置与姿态均不受控制的漂浮基两杆空间机械臂系统的控制问题.系统动力学分析的结果表明,结合系统动量及动量矩守恒关系得到的系统动力学方程将为系统惯性参数的非线性函数.证明了借助于增广变量法,即通过适当扩展系统的控制输入与输出可以得到一组控制方程,它们可以表示为一组适当选择的惯性参数的线性函数.以此为基础,针对机械臂末端载荷参数未知的情况,设计了关节空间轨迹跟踪的增广自适应控制方案.此控制方案的显著优点在于不需要测量漂浮基的位置及移动的速度、加速度.仿真运算证实了方法的有效性.      

空间机器人的目标捕获自适应控制

首先推导了基座姿态受控空间机器人系统运动学关系,得到了广义雅可比矩阵。根据目标的运动来规划机械臂末端在惯性空间的期望轨迹。对机器人动力学和运动学关系式进行线性参数比,分别对动力学待估参数和运动学待估参数设计在线修正律,在关节空间采用自适应控制。对于存在动力学参数不确知的机器人系统,算法保证了系统的渐近稳定,在成目标捕获任务的同时,控制基座姿态保持在期望范围之内。以平面两关节空间机器人系统为对象进行了仿真,结果表明了算法的可行性和有效性。     

双臂空间机器人关节运动的一种增广自适应控制方法

讨论了载体位置、姿态均不受控制情况下,具有未知参数的自由漂浮双臂空间机器人系统的自适应控制问题.由于此类机器人系统具有结合系统动量及动量矩守恒关系得到完全能控形式的系统动力学方程,以及系统惯性参数不符合惯常的线性函数关系的特点,因而地面机器人的控制方法在此难以直接推广应用.为了克服上述难点,仅将系统动量守恒关系耦合到系统动力学方程当中,而不耦合系统动量矩守恒关系,结果得到一组欠驱动形式的系统动力学方程.该系统动力学方程的优点是关于一组组合惯性参数能保持惯常的线性函数关系.以此为基础,并借助增广变量法,针对双臂空间机器人末端爪手所持载荷参数未知的情况,设计了关节空间轨迹跟踪的自适应控制方案.该控制方案的显著优点为,不需要测量、反馈双臂空间机器人漂浮基的位置、移动速度和移动加速度.系统的数值仿真,证实了方法的有效性.      

State estimate for stochastic systems with dual unknown interference inputs

Stochastic system state estimation subject to the unknown interference input widely exists in many fields, such as the control, communication, signal processing, and fault diagnosis. However, the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input, and the state model and the measurement model are both with the same unknown interference input. State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs (dual-UI) with different physical meanings and mathematical definitions is concerned here. Firstly, the decoupling condition with the Unknown Interference input in the State model (S-UI) is shown, which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs (M-UI) appearing in the state model and the measurement model. Then, through defining the Differential term of the adjacent M-UI (M-UID), the equivalent system with only M-UID in the state model is obtained. Finally, considering the design freedom of the equivalent system, the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate, respectively. Two simulation cases verify the effectiveness and superiority compared with the traditional methods.     

Hypersonic vehicle aerodynamic design using modified sequential approximate optimization

Hypersonic vehicles are receiving increased attention within the aerospace community due to their high cruise speed and long-range capabilities. In this paper, a modified Sequential Approximate Optimization method is proposed for an optimized aerodynamic design of a hypersonic vehicle. As part of this approach, a constrained experimental design method is developed to handle the constraints more efficiently. A radial basis function is used to surrogate time-consuming CFD analysis. An efficient and more robust numerical mesh morphing scheme for the hypersonic vehicle is developed for the generation of high-quality meshes. Within this paper, a novel adaptive infilling strategy is proposed which uses an inaccurate search technique coupled with an elite archive. This allows the location of a more promising sample region and hence improves the surrogate accuracy, thereby further enhancing the optimization efficiency. A hypersonic vehicle aerodynamic design problem is solved using the proposed approach and satisfactory results are obtained at much lower computational costs. The lift-to-drag ratio is increased by 23.8% when compared with the base configuration while also satisfying the volume and lift constraints. The pressure and Mach contours have been compared with those of the base configuration and the results demonstrate the strength of the optimized configuration. The modified sequential approximate optimization for designing an improved hypersonic vehicle is worth referencing in future work.     

导弹自动驾驶仪微机自适应控制系统设计

研究了战术导弹自动驾驶仪的微计算机系统设计问题，讨论自动驾驶仪采用衰减记忆最小二乘法直接辨识弹体的时变参数，应用最小方差着适应控制方法计算出反馈控制量，实现闭环自适应控制。文中根据地空导弹自导弹自动驾驶仪以微机系统的功能要求，论证了微机系统总休性能参数的选择，设计出Ｚ－８０００ＣＰＵ为核心的微机系统，推导出一套适合微机定点运算的算法算式，并在此基础上，编制了微机系统的应用软件。计算结果表明，用微处     

用自联想网络处理带噪声的发动机数据

研究了用自联想网络(AANN)进行数字滤波的方法。自联想网络采用一种带有瓶颈层的特殊结构，且具有单位总增益。在经过大量带噪声样本的训练之后，各变量之间能够建立起内在联系。输入信息通过瓶颈层前的压缩及瓶颈层后的解压缩过程，信息中的精华将被提取，从而使人们能够利用冗余信息抑制其测量噪声，使发动机测量参数在最大程度上减少噪声对其带来的负面影响。     

In-process adaptive milling for large-scale assembly interfaces of a vertical tail driven by real-time vibration data

Assembly interfaces, the joint surfaces between the vertical tail and rear fuselage of a large aircraft, are thin-wall components. Their machining quality are seriously restricted by the machining vibration. To address this problem, an in-process adaptive milling method is proposed for the large-scale assembly interface driven by real-time machining vibration data. Within this context, the milling operation is first divided into several process steps, and the machining vibration data in each pro...     

地磁定位方法综述

地磁导航具有可用区域广泛、无累积误差、无源和隐蔽性强等优势,是未来定位导航与授时（PNT）体系中潜在的重要导航定位手段之一。地磁导航技术包括磁场信息的测量、地磁基准图的建立和地磁定位方法的设计3个重要内容。本文主要围绕地磁定位方法,调研总结了当前主流的地磁滤波、地磁匹配和磁场同时定位与构图(SLAM)三类方法的原理及技术发展路线,重点分析了不同方法的优缺点、适用场景、时效性、对磁图和传感器的需求,并对地磁定位方法的发展方向进行了展望。     

红外地平仪摆动扫描装置自适应控制器的FPGA实现

本文介绍了红外地平仪自适应摆动控制器ＦＰＧＡ原理样机的有关研制结果。针对新型长寿命红外地平仪的摆动扫描控制装置，基于系统特征分析，提出了能跟踪摆动装置的固有频率、同时保证摆幅稳定的一套自适应控制方案，并且研制出ＦＰＧＡ芯片原理样机，最终通过了实验验证并得到满意的实验结果。