绳系网捕系统的定位与测姿方法研究

基于双目视觉原理,建立了空间目标的三维坐标计算模型,利用安装在捕获端的摄像头对主星进行观测,建立了捕获端定姿方法.仿真算例验证了所提方法能够以较高的测量精度实现定位和测姿,可以满足绳系卫星捕获端的姿态确定精度需求.     

一种共轴式直升机操纵机构的运动学建模与分析

 共轴式直升机操纵机构的输入/输出运动学关系复杂、非线性严重,不同通道间控制耦合大,其中航向采用全差动的操纵机构最为复杂。为了分析用比例关系简化建模所引起的误差及利用逆运动学进行操纵系统线性化,必须对操纵机构运动学进行精确建模。针对一种航向全差动操纵机构,首先,运用机构学原理,通过去除过约束、局部自由度对机构进行简化,计算得到操纵机构自由度;然后,将操纵机构分为3个子模块,通过对每个模块应用空间机构位置分析方法进行正向、逆向运动学推导,建立系统完整的运动学模型;利用光学测量原理设计了测试系统,并通过实验验证了所建模型的正确性;最后给出了所建模型在共轴式直升机建模、操纵解耦及线性化方面的应用方法。     

主被动复合驱动自适应指爪机构的抓取模式分析

为了满足空间在轨服务任务的多样化需求,基于主被动复合驱动思想提出一种自适应末端操作器——二指连杆欠驱动指爪机构,并对其抓取模式进行定量分析。首先,在描述指爪机构运动学关系的基础上,根据虚功原理建立机构的静力平衡方程。在此基础上,对其进行静力学分析可知,机构平衡状态下与目标物的接触力不仅取决于机构的几何尺寸,还与接触点位置有关;而机构的抓取模式取决于约束空间内系统的受力情况,因此该指爪能够根据不同形状目标物与机构接触点位置的不同,自适应地选择抓取模式,包括平行抓取、包络抓取等。最后,通过实验样机对不同形状物体进行抓取实验,验证了指爪机构抓取目标的自适应性,为后续的机构设计和控制应用奠定理论和技术基础。     

空间目标光电巡天策略的优化

随着空间目标与碎片数量的激增,传统的基于目标跟踪的空间目标光电监视手段已不能满足需求,近年出现了面向空域的空间目标巡天观测。针对空间目标巡天观测的特点,同时考虑空间目标观测的目标个数和数据量,提出了一种空间目标巡天观测策略,并建立了相应的空间目标光电巡天优化数学模型。模型中通过0-1变量的使用,实现了目标函数和约束条件的线性化,十分有利于大规模问题的求解,能够更好地满足实际需求。仿真计算表明:策略简单,易于实现,并且有很好的效果;通过优化,只需要少量望远镜即能实现大批量空间目标的监视,并保持一定的观测数据量,为空间目标光电监视策略提供了新的思路。     

一种长行程小型化对接机构设计与分析

针对故障航天器和太空垃圾的在线对接与操作问题,基于非合作目标对接技术的要求和特点,提出了一种以卫星远地点发动机喷管为对接接口的长行程小型化的对接机构方案。设计了对接机构的具体结构并建立其三维模型,并根据此模型,对对接机构的包络范围进行了求解分析;使用ADAMS软件对机构进行了动力学仿真,研究了对接过程中目标喷管的运动学特性,分析了末端机构与目标的碰撞接触情况及机械臂中各关节受力情况。计算与仿真结果表明:所提对接机构能够对目标进行有效、可靠的对接。     

一种复杂空间飞网系统参数优化设计方法

由轻质软绳索编织而成的空间飞网是为非合作目标捕获而提出的空间系统概念,在空间碎片和废弃航天器处理方面具有很大的应用潜力。从平台抛射出后,飞网在空间形成不稳定的网形,且网形变化规律受初始参数设计的影响较大。针对空间飞网系统设计与试验中系统参数匹配问题,本文提出以容错值作为飞网展开性能的定量描述,从捕获任务的层面,建立面向捕获容错的空间飞网系统参数优化数学模型;以抓捕固定距离、确定大小的目标任务为算例,联合Isight优化平台与ANSYS/LS-Dyna求解,得到飞网系统最优参数匹配,算例仿真结果表明结果的适用性;最后,利用试验设计和极差分析方法验证最优点的稳定性。研究的模型与方法为开展空间飞网系统地面及空间试验等工程应用提供理论依据。     

基于模糊PID算法的六自由度并联机构控制研究

针对六自由度并联机构难以实现高精度及快速响应的问题,分析六自由度并联机构模型,提出基于模糊PID的六自由度并联机构的控制算法.介绍了六自由度并联机构的运动学反解模型及机械系统模型;在此基础上确定模糊算法的模糊语言变量、隶属函数和模糊规则,完成了六自由度并联机构模糊PID控制器的设计.针对一组PID控制参数进行了仿真和实验,结果表明,加入模糊算法的PID控制提高了系统的动态响应特性及运动精度.     

过重力补偿GPS/INS末制导炮弹弹道仿真研究

针对采用GPS/INS的复合制导炮弹,采用比例导引作为末制导的导引规律,从制导炮弹弹体运动学和动力学方程出发,进行了低成本组合导航系统的设计,建立了惯导系统的误差模型。针对位置、速度的组合方式,采用卡尔曼滤波算法,完成了组合导航系统的信息融合。根据超远程炮弹的弹道特点,进行了末制导段过重力补偿设计。全弹道仿真计算结果表明,该制导控制系统性能良好,可以精确地将制导炮弹导引到目标捕获区,实现以小脱靶量、大落角对目标的攻击。     

基于LSTM的空间机器人系统惯性张量在轨辨识

在空间机器人抓捕目标的过程中,整个系统的惯性张量会随时间变化且在目标被捕获瞬间发生突变,这会严重影响整体姿态控制的精度。针对以上问题,提出了一种基于长短期记忆（LSTM）的系统惯性张量在轨实时辨识方法。首先,对于目标捕获前后的2个阶段,利用拉格朗日方程建立了空间机器人的动力学模型;然后,基于所建空间机器人模型采用域随机化方法生成足量训练数据,并用其对由LSTM网络与多层全连接网络构建的参数辨识网络进行训练;最后,使用训练好的参数辨识网络对系统惯性张量进行辨识。数值仿真结果表明：所提方法能够精确辨识空间机器人抓捕过程中的系统惯性张量,所研究系统的主惯量平均相对辨识误差小于0.001,惯性积的平均相对辨识误差小于0.01。     

空间机器人的若干前沿领域:研究进展和关键技术

基于空间环境和在轨任务的特殊性导致的空间机器人不同于地面机器人的特点,讨论了面向航天产业的核心技术路线图的确定方法,论述了航天员心理陪护机器人的要求和研究方法,重点分析了非合作目标捕获过程面临的非线性碰撞接触动力学等前沿科学问题和冲击载荷下空间漂浮系统的稳定控制等关键技术;并针对未来空间装备巨型化趋势,介绍了大型机械臂研制、多机器人协调和大延迟下对机器人系统智能化的研究进展。     

压电陶瓷叠层作动器迟滞蠕变非线性自适应混合补偿控制方法

压电陶瓷叠层作动器的迟滞蠕变非线性特性严重影响了控制系统的稳定性及动态跟踪精度。针对其迟滞蠕变非线性补偿控制问题,提出了一种高精度动态补偿压电陶瓷叠层作动器非线性特性的自适应混合补偿控制方法,即迟滞蠕变前馈补偿与自适应滤波反馈补偿结合的前馈-反馈混合控制方法。采用改进的Prandtl-Ishlinskii（Modified Prandtl-Ishlinskii,MPI）模型对压电陶瓷叠层作动器迟滞蠕变非线性特性进行精细化建模,并得到其逆补偿模型进行前馈补偿。根据前馈补偿误差,采用自适应滤波反馈控制对输入信号进行实时调控,实现对压电陶瓷叠层作动器的迟滞非线性及lg（t）型蠕变特性的实时精确补偿控制。数值仿真与实验结果表明,相比于常规前馈迟滞蠕变补偿,所提出的自适应混合补偿控制方法可以有效降低压电陶瓷叠层作动器的迟滞补偿误差,极大提高了迟滞蠕变非线性动态跟踪精度以及自适应性。     

GNSS多系统RTK授时性能分析

RTK授时不依赖实时精密星历，精度高、实现简单，在短距离精密授时与时间同步中具有突出的应用潜力。针对城域环境下单系统RTK授时可能面临可用卫星数量较少、收敛时间较长等问题，验证分析了GNSS多系统RTK授时性能。基于中国科学院国家授时中心时间频率资源和3个GNSS跟踪站的BDS-3、GPS和Galileo观测数据开展多系统RTK授时试验，涉及动态、静态和固定站坐标3种模式，并从授时精度、收敛时间和稳定度3个方面展开分析。两条基线的试验结果表明：与光纤双向时间频率传递结果相比，动态模式下，多系统单频授时差异STD较GPS单系统分别提高9.13%和9.01%，静态模式分别提高6.09%和11.76%，固定站坐标模式分别提高3.04%和5.79%，多系统单频RTK授时的授时结果差异STD优于0.25 ns，双频优于0.15 ns；多系统融合使得RTK授时的收敛时间与GPS单系统相比至少缩短25%以上，静态模式下双频RTK收敛时间缩短最多，两条基线分别缩短66.9%和67.8%；3种模式多系统站间钟差的万秒稳均进入10-15量级，动态模式和静态模式下短期稳定度相比GPS单系统有明显改善，但随着平均时间的增长，这种改善也在逐渐减弱。试验结果可为城域环境下GNSS多系统RTK授时的应用推广提供一定的参考。     

Fuzzy adaptive robust control for space robot considering the effect of the gravity

Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control（FARC） strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative（PD） controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.     

Robust Control for Static Loading of Electro-hydraulic Load Simulator with Friction Compensation

Load simulator is a key test equipment for aircraft actuation systems in hardware-in-the-loop-simulation. Static loading is an essential function of the load simulator and widely used in the static/dynamic stiffness test of aircraft actuation systems. The tracking performance of the static loading is studied in this paper. Firstly, the nonlinear mathematical models of the hydraulic load simulator are derived, and the feedback linearization method is employed to construct a feed-forward controller to improve the force tracking performance. Considering the effect of the friction, a LuGre model based friction compensation is synthesized, in which the unmeasurable state is estimated by a dual state observer via a controlled learning mechanism to guarantee that the estimation is bounded. The modeling errors are attenuated by a well-designed robust controller with a control accuracy measured by a design parameter. Employing the dual state observer is to capture the different effects of the unmeasured state and hence can improve the friction compensation accuracy. The tracking performance is summarized by a derived theorem. Experimental results are also obtained to verify the high performance nature of the proposed control strategy.     

基于FPGA的北斗B1频点接收机 基带信号处理器设计

针对北斗二代B1频点信号比特翻转频繁的问题,设计并实现了基于FPGA的北斗B1频点导航接收机基带处理器.该处理器在信号捕获过程中设计了频率精细搜索的精捕获算法,避免了假捕获并且提高了捕获频率的精度;在载波跟踪环路中设计2阶锁频环辅助3阶锁相环的方案,以提高环路跟踪的动态性能.其中,锁频环和锁相环均设计了对比特翻转敏感的鉴别器,保证环路跟踪的准确性.试验结果表明,该基带处理器设计具有较高精度的捕获频率和良好的高动态跟踪能力.     

Tracking with classification-aided multiframe data association

In most conventional tracking systems, only the target kinematic information from, for example, a radar or sonar or an electro-optical sensor, is used in measurement-to-track association. Target class information, which is typically used in postprocessing, can also be used to improve data association to give better tracking accuracy. The use of target class information in data association can improve discrimination by yielding purer tracks and preserving their continuity. In this paper, we present the simultaneous use of target classification information and target kinematic information for target tracking. The approach presented integrates target class information into the data association process using the 2-D (one track list and one measurement list) as well as multiframe (one track list and multiple measurement lists) assignments. The multiframe association likelihood is developed to include the classification results based on the "confusion matrix" that specifies the accuracy of the target classifier. The objective is to improve association results using class information when the kinematic likelihoods are similar for different targets, i.e., there is ambiguity in using kinematic information alone. Performance comparisons with and without the use of class information in data association are presented on a ground target tracking problem. Simulation results quantify the benefits of classification-aided data association for improved target tracking, especially in the presence of association uncertainty in the kinematic measurements. Also, the benefit of 5-D (or multiframe) association versus 2-D association is investigated for different quality classifiers. The main contribution of this paper is the development of the methodology to incorporate exactly the classification information into multidimensional (multiframe) association.     

Spacecraft attitude/rate estimation using vector-aided GPSobservations

A sequential filtering algorithm is presented for spacecraft attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the state of the filter, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the robustness and accuracy of the method. Numerical examples are used to demonstrate the performance of the method     

Geometric error analysis of an over-constrained parallel tracking mechanism using the screw theory

This paper deals with geometric error modeling and sensitivity analysis of an overconstrained parallel tracking mechanism. The main contribution is the consideration of overconstrained features that are usually ignored in previous research. The reciprocal property between a motion and a force is applied to tackle this problem in the framework of the screw theory. First of all, a nominal kinematic model of the parallel tracking mechanism is formulated. On this basis, the actual twist of the moving platform is computed through the superposition of the joint twist and geometric errors. The actuation and constrained wrenches of each limb are applied to exclude the joint displacement. After eliminating repeated errors brought by the multiplication of wrenches, a geometric error model of the parallel tracking mechanism is built. Furthermore,two sensitivity indices are defined to select essential geometric errors for future kinematic calibration. Finally, the geometric error model with minimum geometric errors is verified by simulation with SolidWorks software. Two typical poses of the parallel tracking mechanism are selected, and the differences between simulation and calculation results are very small. The results confirm the correctness and accuracy of the geometric error modeling method for over-constrained parallel mechanisms.     

Practical compensation for nonlinear dynamic thrust measurement system

The real dynamic thrust measurement system usually tends to be nonlinear due to the complex characteristics of the rig, pipes connection, etc. For a real dynamic measuring system,the nonlinearity must be eliminated by some adequate methods. In this paper, a nonlinear model of dynamic thrust measurement system is established by using radial basis function neural network(RBF-NN), where a novel multi-step force generator is designed to stimulate the nonlinearity of the system, and a practical compensation method for the measurement system using left inverse model is proposed. Left inverse model can be considered as a perfect dynamic compensation of the dynamic thrust measurement system, and in practice, it can be approximated by RBF-NN based on least mean square(LMS) algorithms. Different weights are set for producing the multi-step force, which is the ideal input signal of the nonlinear dynamic thrust measurement system. The validity of the compensation method depends on the engine’s performance and the tolerance error0.5%, which is commonly demanded in engineering. Results from simulations and experiments show that the practical compensation using left inverse model based on RBF-NN in dynamic thrust measuring system can yield high tracking accuracy than the conventional methods.     

Capture and detumbling control for active debris removal by a dual-arm space robot

Active debris removal (ADR) technology is an effective approach to remediate the proliferation of space debris, which seriously threatens the operational safety of orbital spacecraft. This study aims to design a controller for a dual-arm space robot to capture tumbling debris, including capture control and detumbling control. Typical space debris is considered as a non-cooperative target, which has no specific capture points and unknown dynamic parameters. Compliant clamping control and the adaptive backstepping-based prescribed trajectory tracking control (PTTC) method are proposed in this paper. First, the differential geometry theory is utilized to establish the constraint equations, the dynamic model of the chaser-target system is obtained by applying the Hamilton variational principle, and the compliance clamping controller is further designed to capture the non-cooperative target without contact force feedback. Next, in the post-capture phase, an adaptive backstepping-based PTTC is proposed to detumble the combined spacecraft in the presence of model uncertainties. Finally, numerical simulations are carried out to validate the feasibility of the proposed capture and detumbling control method. Simulation results indicate that the target detumbling achieved by the PTTC method can reduce propellant consumption by up to 24.11%.