空间系绳系统展开的滑模变结构控制

为了增强空间系绳系统展开过程的抗干扰性,本文提出了空间系绳系统展开运动轨迹跟踪的滑模变结构控制方法.考虑大气摄动和无模型摄动建立了空间系绳系统展开运动动力学模型.基于遗传算法,针对两阶段展开方式,采用最优振荡阻尼张力控制律和等分时张力控制律设计了展开运动标称轨迹.为了实现轨迹的鲁棒跟踪,采用考虑展开长度的等效控制和连续函数幂次趋近律切换控制设计了滑模变结构控制器.仿真结果表明,所提出的控制方法有效增强了空间系绳系统展开运动的动态性能及鲁棒性.     

输入有界的自由漂浮柔性空间机器人轨迹跟踪控制

针对自由漂浮柔性空间机器人轨迹跟踪控制问题, 首先利用拉格朗日和假设模态法建立了动力学模型. 分析系统动力学模型, 综合考虑欠驱动、柔性振动等特点, 将其简化为一种带有柔性振动扰动完全可控的动力学模型; 在此基础上, 考虑控制输入受限, 提出一种自适应状态反馈控制策略. 该策略采用自适应技术实时在线学习柔性振动扰动参数, 从而保证控制律对柔性振动扰动具有良好的鲁棒性; 最后, 基于Lyapunov方法证明了该控制策略能够实现关节期望轨迹的跟踪. 仿真验证了该控制策略对控制输入受限系统轨迹跟踪控制的有效性和可靠性.     

空间机器人捕获运动目标的协调规划与控制方法

针对目标以任意轨迹运动且其轨迹可能与``有保证工作空间'不相交的问题, 提出了空间机器人捕获运动目标的协调规划与控制方法. 首先, 根据手眼视觉测量数据, 预测目标的运动路径, 由此确定空间机器人对目标的最优交会姿态及最佳捕获臂型; 其次, 规划基座姿态及机械臂关节角的轨迹; 最后, 采用协调控制的方法, 实现空间机器人系统对运动目标的最优捕获(以最优交会姿态及最佳捕获臂型对目标进行捕获). 仿真结果表明了该方法的有效性.     

空间机器人最优能耗捕获目标的自适应跟踪控制

提出了一种能够引导末端执行器以期望速度跟踪目标的轨迹规划方法。该方法可以实现避障并满足关节限制要求。基于轨迹规划方法,设计了一种利用自由飘浮空间机器人跟踪与捕获章动自旋卫星的自适应控制策略。此外,该控制策略还考虑了最优能耗、测量误差和优化误差。首先,为了使执行器的跟踪误差和机械臂的能耗最小,将空间机器人的控制策略描述为一个关于关节速度、力矩和避障距离的不等式约束优化问题。然后,推导出一个系数为下三角矩阵的显式状态方程,并对目标函数进行解耦和线性化。设计了一种关节速度和力矩分段优化方法去代替传统的凸二次规划方法求解最优问题,这种方法具有较高的计算效率。最后,利用李雅普诺夫稳定性理论验证了所提控制方法的收敛性。     

基于遗传算法的机器人关节空间最优运动规划

本文整体上研究了最优轨迹规划问题，它包含两个密切相关的子问题，最优路径规划和最优轨迹规划，本文提出了一种基于遗传算法的更为一般，柔性和有效的新方法，该策略综合考虑了机器人的运动学约束，动力学约束和控制约束，最优轨迹用合适的多项式拟合，得到的控制序列适宜于高速高精度的动力学控制，本文最后以二自由度机器人为例进行了仿真实验。     

无人动力伞在线子空间预测控制

针对无人动力伞(UPP)的飞行具有不确定性、非线性和复杂性的特点,建立了无人动力伞6自由度非线性动力学模型,仿真分析了模型对输入信号的响应特性.提出了无人动力伞在线子空间预测控制算法.该算法能及时地克服模型失配、时变及干扰等对飞行控制系统的影响,使有约束的预测控制能够在控制时域内保持最优.仿真结果表明,该算法能有效辨识仿真模型产生的输入输出数据,表现出了较好的跟踪性能和控制精度.     

空间柔性双臂机器人的神经网络协调控制

基于对机器人闭链系统运动特性的分析,采用假设模态法及拉格朗日方程建立了自由浮动空间柔性双臂机器人协调操作刚性负载闭链系统的动力学模型,然后采用基于小脑模型的模糊神经网络与非线性PD并行控制的方法对该动力学模型进行轨迹跟踪,并对内力采用积分控制;通过仿真实验比较,该方法比一般的非线性PD控制,在跟踪误差、抗干扰性、鲁棒性方面,都有很大的改善.     

基于微分平坦三轮全向足球机器人的轨迹规划

针对三轮全向足球机器人路径规划、位姿控制的特点,讨论了轨迹规划的控制问题,提出了一种基于微分平坦理论的轨迹规划的控制算法。此算法在轨迹跟踪控制中用来生成可行的期望轨迹,在路径规划的基础上研究三轮全向足球机器人动力学模型的轨迹规划方法,并且同时考虑控制量约束下的最优轨迹生成。仿真及实验结果表明,该算法具有控制精度较高,实时性强的特点。     

基于遗传算法的多机器人系统最优轨迹规划

针对关节型多机器人系统在静态环境下的点到点的轨迹规划问题,提出了一种基于遗传算法的最优轨迹规划策略.采用遗传算法在综合考虑各机器人沿轨迹运动的安全性、运动代价以及运动学约束的基础上为单个机器人规划最优的运动轨迹,并通过协调各机器人沿预定轨迹运行的时间避免机器人之间碰撞的发生.针对含有3个二自由度平面关节型机器人的多机器人系统进行了仿真实验,实验结果验证了该方法的有效性.     

自由漂浮空间机器人避奇异规划—跟踪算法

针对路径相关空间内自由漂浮空间机器人无法进行有效跟踪控制的问题,设计了一种避奇异轨迹规划—跟踪算法,用于完成路径相关空间机械臂末端轨迹跟踪控制的任务．首先,分析奇异条件并设定安全边界曲线,求解回避奇异的基座姿态角阈值,从而得到避奇异参考轨迹及初始状态值．接着,利用自由漂浮空间机器人非线性动力学模型具有状态依赖参数的类线性结构特点,基于状态依赖Riccati方程设计跟踪控制器对末端速度进行跟踪,保证闭环系统的局部渐近稳定性．所提方法克服了传统方法将工作空间约束在路径无关空间的缺点．仿真结果表明,该算法具有比比例微分（proportional derivative,PD）控制更高的跟踪精度．同时,在存在输入干扰的情况下仍然能够实现有效跟踪．     

Coordinated control method of space-tethered robot system for tracking optimal trajectory

Space-tethered robot system is a new kind of space robot, which consists of a robot platform, space tether, and operation robot. This paper presents the coordinated control method in order to save thruster fuel of operation robot in the process of tracking the optimal approach trajectory. First, the optimal approach trajectory of an operation robot is designed using the Gauss pseudospectral method, which resulted in continuous optimal control force using the Lagrange interpolation scheme. The optimal control force is optimized and distributed to space tether and thrusters through simulated annealing algorithm in discrete points, which minimized fuel consumption of thrusters. The distributive continuous force is obtained via cubic polynomial fitting of optimal distributive force in 0.1s discrete time point. To tracking the optimal trajectory, Fuzzy Proportional-Derivative controller is designed with the help of optimal distribution force which come from optimization model. Simultaneously, the relative attitude of the operation robot is stabilized using attitude time-delay algorithm through the reaction wheels. Numerical results are presented, demonstrating the validity of saving thruster fuel and well performance in tracking the optimal trajectory.

     

Postcapture robust nonlinear control for tethered space robot with constraints on actuator and velocity of space tether

Stabilization control is an essential mission for the tethered space robot‐target combination during the postcapture phase of tethered space robot (TSR). In this paper, the stabilization problem of such a tumbling combination is studied. With the consideration of the space tether and the attitude of the TSR's gripper, the dynamic model of the combination is first derived using Lagrange method. Then a robust nonlinear controller for the combination is proposed based on the backstepping control method. Considering the constraint on the velocity of the space tether, command filter method is utilized to guarantee the velocity of the space tether within a permitted range. A feedback term is designed to compensate the saturation of the thruster. Moreover, an adaptive law is designed to estimate the disturbance of parameter uncertainties and this disturbance is compensated in the proposed controller. Numerical simulations suggest that the proposed robust controller can realize the orbit and attitude stabilization of the combination; besides, the velocity of the space tether is effectively constrained and the parameter uncertainties of the combination can be compensated via the adaptive law. Copyright © 2016 John Wiley & Sons, Ltd.     

Robust Tracking Control of a Quadrotor Helicopter

In this paper, a robust tracking control method for automatic take-off, trajectory tracking, and landing of a quadrotor helicopter is presented. The designed controller includes two parts: a position controller and an attitude controller. The position controller is designed by the static feedback control method to track the desired trajectory of the altitude and produce the desired angles for pitch and roll angles. By combining the proportional-derivative (PD) control method and the robust compensating technique, the attitude controller is designed to track the desired pitch and roll angles and stabilize the yaw angle. It is proven that the attitude tracking error of each channel can converge to the given neighborhood of the origin ultimately. Experimental results demonstrate the effectiveness of the designed control method.     

State Space Constrained Iterative Learning Control for Robotic Manipulators

Real‐life work operations of industrial robotic manipulators are performed within a constrained state space. Such operations most often require accurate planning and tracking a desired trajectory, where all the characteristics of the dynamic model are taken into consideration. This paper presents a general method and an efficient computational procedure for path planning with respect to state space constraints. Given a dynamic model of a robotic manipulator, the proposed solution takes into consideration the influence of all imprecisely measured model parameters, making use of iterative learning control (ILC). A major advantage of this solution is that it resolves the well‐known problem of interrupting the learning procedure due to a high transient tracking error or when the desired trajectory is planned closely to the state space boundaries. The numerical procedure elaborated here computes the robot arm motion to accurately track a desired trajectory in a constrained state space taking into consideration all the dynamic characteristics that influence the motion. Simulation results with a typical industrial robot arm demonstrate the robustness of the numerical procedure. In particular, the results extend the applicability of ILC in robot motion control and provide a means for improving the overall trajectory tracking performance of most robotic systems.     

Fuzzy PID control of space manipulator for both ground alignment and space applications

Considering gravity change from ground alignment to space applications, a fuzzy proportional-integral-differential (PID) control strategy is proposed to make the space manipulator track the desired trajectories in different gravity environments. The fuzzy PID controller is developed by combining the fuzzy approach with the PID control method, and the parameters of the PID controller can be adjusted on line based on the ability of the fuzzy controller. Simulations using the dynamic model of the space manipulator have shown the effectiveness of the algorithm in the trajectory tracking problem. Compared with the results of conventional PID control, the control performance of the fuzzy PID is more effective for manipulator trajectory control.     

基于非线性制导的四旋翼轨迹跟踪控制

四旋翼是一种欠驱动、强耦合的可垂直起降的飞行器,为了实现其能够以设定速度跟踪空间轨迹,设计了一种基于非线性制导算法的轨迹跟踪控制方法。该方法分为了导引与控制两部分组成,导引部分以任务轨迹与期望速度为输入量通过非线性制导算法输出当前四旋翼的期望加速度,控制部分以得到的期望加速度为输入量采用串级PID算法对四旋翼进行姿态控制,从而实现四旋翼保持设定速度对任务轨迹的跟踪。仿真结果表明,所提方法能够实现四旋翼对复杂任务轨迹的精确跟踪,二维复杂轨迹跟踪距离偏差不超过±0.6m,速度偏差不超过2m/s;三维复杂轨迹除了受自身控制力限制的飞行段外,跟踪距离偏差基本控制在±4m以内,速度偏差不超过2m/s。     

Adaptive iterative learning controller with input learning technique for a class of uncertain MIMO nonlinear systems

In this paper, an adaptive iterative learning controller (AILC) with input learning technique is presented for uncertain multi-input multi-output (MIMO) nonlinear systems in the normal form. The proposed AILC learns the internal parameter of the state equation as well as the input gain parameter, and also estimates the desired input using an input learning rule to track the whole history of command trajectory. The features of the proposed control scheme can be briefly summarized as follows: 1) To the best of authors’ knowledge, the AILC with input learning is first developed for uncertain MIMO nonlinear systems in the normal form; 2) The convergence of learning input error is ensured; 3) The input learning rule is simple; therefore, it can be easily implemented in industrial applications. With the proposed AILC scheme, the tracking error and desired input error converge to zero as the repetition of the learning operation increases. Single-link and two-link manipulators are presented as simulation examples to confirm the feasibility and performance of the proposed AILC.

     

卫星姿态直接自适应模糊预测控制

对具有模型不确定性和未知外干扰的卫星姿态系统提出了多输入多输出直接自适应模糊预测跟踪控制设计方法. 此方法先基于卫星姿态动力学模型设计出非线性广义预测控制律, 再构造直接自适应模糊控制器逼近预测控制律中因模型不确定性引起的未知项. 文中证明了所设计的控制律能使卫星跟踪给定的期望姿态轨迹, 跟踪误差收敛到原点的小邻域内. 仿真结果验证了此方法的有效性.     

基于三步法的机械臂轨迹跟踪控制

考虑机械臂末端轨迹跟踪控制问题,以跟踪逆运动学求解出的末端期望轨迹对应的各关节期望角度为控制目标.设计了一种基于三步法的控制器,该控制器由类稳态控制、可变参考前馈控制和误差反馈控制3部分组成.证明了该控制器可以通过控制机械臂的各关节力矩实现各关节实际角度对期望角度的状态跟踪,进而使得末端轨迹渐近跟踪期望轨迹,并且跟踪误差是输入到状态稳定的.仿真表明基于三步法控制器的空间机械臂末端可以渐近跟踪期望轨迹,并且该算法可以克服系统的末端负载质量变化等不确定性的影响.