具有时延的漂浮基空间机器人基于泰勒级数预测、逼近的改进非线性反馈控制

 探讨了本体位置与姿态均不受控的漂浮基空间机器人在时间延迟(简称时延)情况下惯性空间轨迹跟踪的控制问题.利用拉格朗日方法并结合系统动量守恒关系,分析、建立了漂浮基空间机器人完全能控形式的系统动力学模型及运动Jacobi关系.以此为基础,针对系统存在时延的情况,利用泰勒级数预测、逼近的方法,建立了适用于时延情况下控制系统设计的数学模型.利用该模型,提出了一种空间机器人在时延情况下的改进非线性反馈控制方案.然后运用Lyapunov第二类方法,结合范数以及图形分析的方法证明了在时延情况下整个闭环控制系统的渐近稳定性.文中提到的控制方案能够有效地克服系统存在时延的影响,控制漂浮基空间机器人末端爪手跟踪惯性空间的期望轨迹.系统数值仿真结果证明了上述控制方案的有效性与精确性.     

参数不确定空间机械臂系统的增广自适应控制

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,为此对系统的运动学、动力学作了分析。结果表明 :结合系统动量守恒及动量矩守恒关系得到的系统广义Jacobi关系、以及系统的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可以将增广广义Jacobi矩阵以及系统动力学方程表示为一组适当选择的惯性参数的线性函数。在此基础上,给出了系统参数未知时,空间机械臂末端抓手跟踪惯性空间期望轨迹的增广自适应控制方案。通过仿真运算,证实了方法的有效性。     

自由漂浮空间机器人点到点避奇异运动控制方法

针对具有冗余机械臂的自由漂浮空间机器人（Free Floating Space Robot, FFSR）点到点避免奇异性规划和控制问题,提出了一种冗余FFSR的点到点避免奇异控制方法。首先,该方法基于离散状态依赖李卡提方程（DSDRE）控制器设计方法,利用FFSR的动力学和运动学方程实现了FFSR系统方程的伪线性重构;然后,基于伪线性重构系统及DSDRE状态调节器设计方法实现了FFSR的关节角速度和末端位姿的同时跟踪控制;其次,根据跟踪控制器对FFSR广义雅克比矩阵（GJM）行满秩的设计要求,定义FFSR的奇异性判别依据,构造了避奇异约束函数;再次,由于冗余FFSR系统具有多逆运动学解特点,考虑关节角及关节角速度约束,结合避奇异约束函数设计了FFSR的期望轨迹在线规划器,进一步将设计的跟踪控制器与规划器相结合提出了冗余FFSR末端点到点避奇异运动控制方法。最后,为验证所提方法的有效性同时考虑简化计算,采用平面4连杆FFSR模型进行数值仿真,仿真结果表明所提点到点避奇异运动控制方法能够有效实现冗余FFSR系统的点到点避奇异运动。     

空间机械臂地面装调与空间应用迭代学习控制

针对空间机械臂系统地面装调和空间应用两阶段的末端轨迹控制问题,提出了采用闭环PD型迭代学习控制算法对空间机器人进行轨迹跟踪控制,从而使在地面重力条件下装调好的空间机械臂能够在空间微重力条件下实现在轨操控任务。建立了空间机械臂在地面装调阶段和空间应用阶段的运动学与动力学模型,给出了控制算法和控制结构,并通过对控制器的收敛性进行分析,给出系统收敛的充分条件。仿真结果表明,采用闭环PD型迭代学习控制算法对轨迹跟踪是有效可行的。     

漂浮基柔性臂空间机器人输出力矩受限的自适应PID输出反馈

针对输出力矩受限的漂浮基柔性臂空间机器人的控制问题,结合系统动量守恒关系和拉格朗日方法建立了系统动力学模型;利用奇异摄动法,慢变子系统设计了输出力矩受限情况下仅有位置传感、建模不确定性及干扰的空间机械臂系统协调运动的自适应PID输出反馈控制算法,快变子系统设计了线性二次最优控制方法主动抑制。该算法采用高精度滤波器估计机器人关节速度,使得整个系统的闭环控制仅需位置输出反馈;在控制率中引入饱和函数,保证输出力矩在给定限制范围内,同时采用自适应PID控制器补偿建模不确定性和干扰。基于Lyapunov稳定性理论证明了该算法可确保控制系统是渐近稳定的,针对平面两关节漂浮基柔性臂空间机器人的仿真结果表明了所提出的控制方案良好的跟踪性和快速收敛性。     

漂浮基空间机器人执行机构部分失效故障的分散容错控制

针对载体位置不受控,姿态受控的漂浮基空间机器人执行机构部分失效故障问题,提出了一种基于有效因子融合的分散滑模神经网络容错控制方案。利用拉格朗日第二类方程建立系统的动力学模型,然后利用分散的思想,将系统分散为若干个子系统,将有效因子融合到子系统的动力学模型中。利用终端滑模进行控制器设计,并利用径向基函数神经网络对系统参数不确定项和未知项进行估计,自适应地补偿了神经网络的估计误差。最后,数值仿真结果表明了提出的分散容错控制器的有效性。     

不确定空间机器人自适应模糊H_∞控制

针对参数不确定及具有外部扰动情况下,载体位置不控、姿态受控的漂浮基空间机器人系统的自适应控制问题,结合系统动量守恒定律,采用拉格朗日第二类方程并建立了完全能控形式的刚性系统动力学方程。为了使系统具有抗扰动能力,将模糊逻辑系统与H_∞控制有机结合,提出了自适应模糊H_∞控制方案,用模糊逻辑系统逼近系统的未知参数部分与并设计了一个H_∞鲁棒控制项用于消除逼近误差,根据Lyapunov方法给出了学习自适应律与H_∞跟踪特性的证明。最后,计算机数值仿真结果表明所提出的控制方案具有可行性。     

基于后退设计的空间机器人系统的自适应控制

 结合后退设计方法和自适应控制理论,对载体姿态可控的空间机器人系统提出了一种自适应跟踪控制算法。当系统的惯性参数未知时,该算法可以保证空间机器人的手端跟踪误差渐近趋于零。和已有的算法相比,所提出的算法可以消除Lyapunov函数导数表达式中的交叉项,明显改善系统的跟踪性能。对平面两关节空间机器人的仿真结果证实了算法的有效性。     

自由漂浮的空间机器人系统的动力学奇异特性分析及其运动规划

首先建立了受非完整约束的自由漂浮空间机器人系统的运动学模型,继而深入分析了系统的动力学奇异性,然后,重点探讨了基于 Lyapunov函数的空间机器人避奇异运动规划方法,最后给出了方法的实例仿真并分析了仿真结果。     

闭链空间机械臂抓持载荷基于积分滑模的模糊自适应控制

讨论了载体位置、姿态均不受控制情况下,漂浮基闭链双臂空间机器人抓持系统的动力学建模与控制问题.利用拉格朗日方法和牛顿-欧拉法,分别建立了双臂空间机器人及抓持负载的动力学模型,并结合漂浮基空间机器人固有的线动量和角动量守恒动力学特性及闭合链约束几何关系,获得了抓持系统合成动力学方程.以此为基础,考虑到闭链双臂空间机器人系统结构的复杂性及某些参数的变动性,根据模糊控制理论和Lyapunov稳定性理论,设计了系统参数不确定情况下该抓持系统基于积分滑模面的力/位置模糊自适应协调控制方案,从而达到对抓持负载位置与所受内力的双重控制效果.系统数值仿真证明了控制方案的有效性与精确性.     

Parameterization and adaptive control of space robot systems

In space application, robot system are subject to unknown or unmodeled dynamics, for example, in the tasks of transporting an unknown payload or catching an unmodeled moving object. We discuss the parameterization problem in dynamic structure and adaptive control of a space robot system with an attitude-controlled base to which the robot is attached. We first derive the system kinematic and dynamic equations based on Lagrangian dynamics and the linear momentum conservation law. Based on the dynamic model developed, we discuss the problem of linear parameterization in term of dynamic parameters, and find that in joint space, the dynamics can be linearized by a set of combined dynamic parameters; however, in inertial space linear parameterization is impossible in general. Then we propose an adaptive control scheme in joint space, and present a simulation study to demonstrate its effectiveness and computational procedure. Because most takes are specified in inertial space instead of joint space, we discuss the issues associated to adaptive control in inertial space and identify two potential problem: unavailability of joint trajectory because the mapping from inertial space trajectory is dynamic-dependent and subject to uncertainty; and nonlinear parameterization in inertial space. We approach the problem by making use of the proposed joint space adaptive controller and updating the joint trajectory by the estimated dynamic parameters and given trajectory in inertial space     

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.     

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%.     

Decentralized adaptive sliding mode control of a space robot actuated by control moment gyroscopes

An adaptive sliding mode control(ASMC) law is proposed in decentralized scheme for trajectory tracking control of a new concept space robot.Each joint of the system is a free ball joint capable of rotating with three degrees of freedom(DOF).A cluster of control moment gyroscopes(CMGs) is mounted on each link and the base to actuate the system.The modified Rodrigues parameters(MRPs) are employed to describe the angular displacements,and the equations of motion are derived using Kane's equations.The controller for each link or the base is designed separately in decentralized scheme.The unknown disturbances,inertia parameter uncertainties and nonlinear uncertainties are classified as a ‘‘lumped" matched uncertainty with unknown upper bound,and a continuous sliding mode control(SMC) law is proposed,in which the control gain is tuned by the improved adaptation laws for the upper bound on norm of the uncertainty.A general amplification function is designed and incorporated in the adaptation laws to reduce the control error without conspicuously increasing the magnitude of the control input.Uniformly ultimate boundedness of the closed loop system is proved by Lyapunov's method.Simulation results based on a three-link system verify the effectiveness of the proposed controller.     

Adaptive control and stabilization of elastic spacecraft

This work treats the question of large angle rotational maneuver and stabilization of an elastic spacecraft (spacecraft-beam-tip body configuration). It is assumed that the parameters of the system are completely unknown. An adaptive control law is derived for the rotational maneuver of the spacecraft. Using the adaptive controller, asymptotically decoupled control of the pitch angle of the space vehicle is accomplished, however this maneuver causes elastic deformation of the beam connecting the orbiter and tip body. For the stabilization of the zero dynamics (flexible dynamics), a stabilizer is designed using elastic mode velocity feedback. In the closed-loop system including the adaptive controller and the stabilizer, reference pitch angle trajectory tracking and vibration suppression are accomplished. Simulation results are presented to show the maneuver capability of the control system     

Model-free adaptive optimal design for trajectory tracking control of rocket-powered vehicle

An adaptive optimal trajectory tracking controller is presented for the Solid-Rocket-Powered Vehicle (SRPV) with uncertain nonlinear non-affine dynamics in the framework of adaptive dynamic programming. First, considering that the ascent model of the SRPV is non-affine, a model-free Single Network Adaptive Critic (SNAC) method is developed based on the dynamic neural network and the traditional SNAC method. This developed model-free SNAC method overcomes the limitation of the traditional SNAC method that can only be applied to affine systems. Then, a closed-form adaptive optimal controller is designed for the non-affine dynamics of SRPVs. This controller can adjust its parameters under different flight conditions and converge to the approximate optimal controller through online self-learning. Finally, the convergence to the approximate optimal controller is proved. The theoretical analysis of the uniformly ultimate boundedness of the tracking error is also presented. Simulation results demonstrate the effectiveness of the proposed controller.     

机器人在轨装配无标定视觉伺服对准方法

针对在轨装配过程中机器人"手眼"关系无法进行有效标定及机器人系统和被操作物惯性参数不定的情况,在传统的无标定视觉伺服基础上设计了深度估计器,基于机器人和图像运动的测量数据在线估计目标特征的深度值,并在机器人关节控制环中设计滑模控制器实时控制机器人关节运动,根据反馈图像信息纠正系统误差完成对准跟踪,通过仿真验证了方法的有效性。所提的无标定视觉伺服对准方法使机器人在装配过程中免去了复杂的"手眼"关系的标定程序,克服了机器人系统及被操作物惯性参数不确定性给装配精度造成的影响,提高了"手眼协调"的鲁棒性,保证机器人能够在复杂的太空环境下完成在轨装配任务。     

近空间可变翼飞行器小翼切换滑模反步控制

针对近空间可变翼飞行器在小翼切换过程中存在参数不确定性的问题,设计了滑模控制和反步法相结合的控制方法以保证飞行器的跟踪性能。首先研究了近空间可变翼飞行器的纵向运动模型,在此基础上设计了速度和高度的反步控制器,同时采用动态面控制方法消除微分膨胀问题,然后结合滑模控制以增强控制器的跟踪性能,最后基于Lyapunov稳定性理论证明了系统的稳定性。仿真结果表明,在参数不确定性时滑模反步控制器能保证系统的稳定性和跟踪性能。