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     

具有神经元网络补偿的隐式广义预测控制的硬件设计与分析

针对隐式广义预测控制算法在被控系统复杂性增加时有效性降低、实时性变差的问题，本文将神经元网络作为该算法的补偿，提出了一种具有神经元网络补偿的隐式广义预测控制方法，并着重讨论了神经元网络的硬件设计和ＮＩＧＰＣ的实现。仿真结果表明：ＮＩＧＰＣ不仅保留了ＩＧＰＣ鲁棒性强等特点，更主要的是它提高了ＩＧＰＣ的的实时性，并使之具有良好的跟踪特性。     

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...     

新型遥测网系统RF链路管理技术

传统的遥测体制已经不能满足日益增长的飞行试验需求,新型TmNS(Telemetry Network System,遥测网系统)需要RF(Radio Frequency,射频)网络管理来协调资源分配,以满足性能要求.首先介绍了TmNS的总体架构,其RF链路除传统下行遥测链路外,新增了一条双向数据链路,实现多个试验对象和多个地面站的组网.随后讨论了该网络系统RF链路管理的原理和流程.由于链路管理器根据网络容量来分配TxOp (Transmission Opportunity,传输机会),故重点研究和比较了2种动态容量分配算法——B-LM算法和E-LM算法,ELM算法较B-LM算法略复杂,但可以减小系统延时,二者可以在链路管理器中共存,依据网络情况进行配置或切换.最后简要分析了链路管理器的软件结构.RF网络管理是TmNS的一项关键技术,该研究将促进我国新一代遥测网的发展.     

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。     

自学习自适应INS／Doppler组合导航系统

本文通过引入文［１］提出的自学习适应Ｋａｌｍａｎ滤波，而将氢此组成的具有自学习功能的智能组合导航系统直接建立在噪声分布密度的异步自学习估计上，由于此时的ＬＡＫＦ在每次重复滤波实验后可离线异步地学习模型与量测噪声的统计特性，从而可有效地避免滤波发散现象并能确保实时性。文中结合某飞行器，对ＩＮＳ／Ｄｏｐｐｌｅｒ组合导航系统进行了仿真研究，所得结果十分满意。     

空间拦截智能自适应变结构导引规律研究

结合空间拦截的精确末制导问题，本文介绍了一种对目标机动和参数摄动具有鲁棒性的自适应结构制导律（ＡＶＳＧ）。在此基础上，我们研究了一种智能自适应变结构制方法（ＩＡＶＳＧ）。此方法精略地估计出目标法向加速度的强度，并以此为依据自主地调整ＡＶＳＧ中变结构项的强度，这样，既可以消除视线角速度的抖动，又可以保证制导精度，仿真结果证明了ＩＡＶＳＧ的有效性。