欠驱动冗余度空间机器人优化控制

欠驱动控制是空间技术中容错技术的重要方面.本文研究了被动关节中有制动器的欠驱动冗余度空间机器人系统的运动优化控制问题.从系统动力学方程出发,分析了欠驱动冗余度空间机器人的优化能力和控制方法;给出了主、被动关节间的耦合度指标;提出了欠驱动冗余度空间机器人系统的“虚拟模型引导控制”方法,在这种方法中采用与欠驱动机器人机构等价的全驱动机器人作为模型来规划机器人的运动,使欠驱动系统在关节空间中逼近给出的规划轨迹,实现了机器人末端运动的连续轨迹运动优化控制;通过末关节为被动关节的平面三连杆机器人进行了仿真,仿真的结果证明了提出算法的有效性.     

含有非驱动关节机器人的学习控制

含有非驱动关节的机器人的运动控制比一般的机器人要困难得多．因为非驱动关节 不能直接控制，系统属于非完全可控系统，一般的光滑反馈控制方法对这样的系统是无效的 ．本文提出了一种学习控制的方法，通过学习获得高精度的前馈控制，实现欠驱动机器人的 高精度运动控制，并在一台实际的欠驱动机器人上进行了实验，给出了实验结果．     

欠驱动柔性机器人的振动可控性分析

欠驱动柔性机器人的可控性分析是对其进行有效控制的关键问题. 本文以具有柔性杆的3DOF平面欠驱动机器人为例, 分两步分析系统的可控性. 首先,忽略杆件的弹性变形, 研究欠驱动刚性系统在不同驱动电机位置的状态可控性；然后, 考虑柔性因素, 研究欠驱动柔性系统的结构振动可控性. 结果表明振动可控性是随机器人关节位形和驱动电机位置而变化的, 并且欠驱动刚性机器人的状态可控性对相应的柔性系统的振动可控性有很重要的影响. 最后, 将上述研究方法扩展到具有一个被动关节的N自由度平面欠驱动柔性机器人.     

基于模糊神经网络的机器人关节驱动补偿控制器

本文提出了一种模糊神经网络控制器,该控制器用于工业机器人关节驱动的位置控制,克服了传统PID很难达到对非线性以及不确定因素的控制效果和简单模糊控制不能完全消除稳态误差的缺点,通过神经网络对模糊规则的学习优化,提高了机器人关节末端位置精度,具有较好控制效果。     

基于平面约束的欠驱动爬壁机器人手眼标定方法

欠驱动机器人因难以像全主动关节机器人一样形成多种空间位姿,故无法直接使用经典的手眼标定方法.为解决这一问题,本文建立了其数学模型,并提出了一种基于平面约束的手眼标定方法.在该方法中,末端执行器的运动被约束于3维空间内的已知平面上,手眼标定的姿态矩阵和平移向量分别通过纯平移与纯旋转运动模式,结合对应的标定图像进行解耦求解.蒙特卡洛仿真实验结果表明,该标定算法有效、准确,且对噪声具有较好的鲁棒性.在所开发的欠驱动爬壁机器人上进行的实际试验中,定位误差被控制在1.5 mm以内.结果表明该标定方法简便易行,精度满足要求.     

基于免疫优化的平面Acrobot线性自抗扰鲁棒镇定

针对受不确定性影响的平面Acrobot机器人,提出一种基于免疫优化的线性自抗扰鲁棒控制设计方法,实现机器人末端点从任意初始位置到达并镇定在目标位置.首先,借助驱动关节与被动关节角度之间的状态约束获取机器人末端点位置与驱动关节角度的对应关系,使末端点的位置控制转换为驱动关节的角度控制;其次,为缩短运动路径加入最小角度位移限制条件,设计免疫算法求解目标位置所对应的驱动关节角度的最小期望值;再次,引入线性自抗扰控制技术,把机器人的模型不确定性、未知干扰等因素视为一个新的扩张状态变量,设计线性扩张状态观测器和基于状态误差的反馈控制器,在仅驱动关节角度可测的情况下实现Acrobot的鲁棒镇定;最后,通过仿真实验验证所提出方法具有更好的鲁棒控制性能.     

PPR型平面欠驱动机械臂的点位控制

研究了PPR型平面欠驱动机械臂(第1个关节和第2个关节是移动关节且是受控的,第3个关节为被动的转动关节)在水平面运动的点位控制问题.首先,通过输入和坐标变换方法,系统的动力学方程被变换成二阶链式形式.其次,提出用反步法推导出保证系统指数渐近稳定的控制器.仿真结果表明,机械臂能够稳定地从任意初始位置运动到任意给定的位置,从而证明了控制器设计的有效性.     

关节联动的单孔手术机器人运动解耦方法

针对单孔腔镜手术机器人的执行器械从驱动空间至操作空间的强运动耦合问题,研究关节联动构型,实现运动解耦,简化运动学模型．首先分析联动构型的运动特性并设计滚轮约束式铰接关节．继而研发了7自由度的联动构型器械,它可实现2自由度的“联动展开”．建立了D-H（Denavit-Hartenberg）模型,分析联动构型器械的位姿分离,并通过解析法直接求解逆运动学．然后基于立体角度量手术器械末端在给定点的灵活度,优化联动构型器械的远端段关节布置．实验表明,联动构型器械末端的姿态只取决于远端段关节,“联动展开”只改变器械末端的位置．驱动空间至关节空间的最大误差小于3°,近端段与远端段的驱动之间互不干扰．     

柔性冗余度机器人残余振动的抑制研究

柔性冗余度机器人兼具柔性机器人与冗余度机器人的特点，在航空航天等领域有着十分广泛的应用前景．但是存在的结构柔性及其引起的振动造成机器人的精确控制极为困难．本文研究了柔性冗余度机器人残余振动的抑制问题，给出了一种控制方法．这种控制方法通过机器人在末端运动停止后依然进行某种自运动对残余振动进行主动的控制，使其迅速衰减．最后通过仿真验证了其可行性     

基于运动学分析的工业机器人轨迹精度测量的研究

机器人关节伺服系统的动态误差,是影响其末端执行器运动轨迹精度的一个重要因 素．本文以六轴关节型激光加工工业机器人为研究对象,采用D-H方法建立起机器人连杆坐 标系,在运动学分析的基础上,运用齐次坐标变换矩阵微分法,建立机器人各关节转角的偏 差值与末端运动轨迹精度之间的模型,并在此基础上,利用机器人与外部的串口通讯,对在 关节伺服系统影响下,沿各种空间位置运动时,机器人末端运动的轨迹精度进行了实际测量 ．     

The dexterity and singularities of an underactuated robot

Underactuated robots are robotic systems with more joints than actuators. A robot may be underactuated by design as in the case of a hyper‐redundant robot with passive joints or may become underactuated as a result of an actuator failure. In this article, we examine the dexterity of underactuated robots whose passive joints operate in either a locked or free‐swinging mode. The ability to an analyze the dexterity of an underactuated robot has important applications especially for the control of passive joints with brakes and for the fault tolerance analysis of an otherwise fully actuated kinematically redundant robot. The approach applied here is to use kinematics and dynamics‐based formulations of manipulator dexterity. We then characterize passive‐joint singularities, i.e., configurations where full end‐effector control is lost because one or more joints are passive instead of active. Lastly, we introduce a new characterization of joint‐limit singularities, which are configurations where full end‐effector control cannot be achieved because one or more joints are at their joint limits. © 2001 John Wiley & Sons, Inc.     

Robust adaptive control of an underactuated free-flying space robot under a non-holonomic structure in joint space

This paper introduces a robust adaptive control scheme for an underactuated free-flying space robot under non-holonomic constraints. An underactuated robot manipulator is defined as a robot that has fewer joint actuators than the number of total joints. Because, if one of the joints is out of order, it is so hard to repair the joint, especially in space, the control of such a robot manipulator is important. However, it is difficult to control an underactuated robot manipulator because of the reduced dimension of the input space, i.e. the non-holonomic structure of the underactuated system. The proposed scheme does not need to assume that the exact dynamic parameters must be known. It is analysed in joint space to control the underactuated robot mounted on the space station under parametric uncertainties and external disturbances. The simulation results have shown that the proposed method is very feasible and robust for a two-link planar free-flying space robot with one passive joint.     

Control of Underactuated Manipulators using Fuzzy Logic Based Switching Controller

This paper introduces a new concept for designing a fuzzy logic based switching controller in order to control underactuated manipulators. The proposed controller employs elemental controllers, which are designed in advance. Parameters of both antecedent and consequent parts of a fuzzy indexer are optimized by using evolutionary computation, which is performed off-line. Design parameters of the fuzzy indexer are encoded into chromosomes, i.e., the shapes of the Gaussian membership functions and corresponding switching indices of the consequent part are evolved to minimize the angular position errors. Such parameters are trained for different initial configurations of the manipulator and the common rule base is extracted. Then, these trained fuzzy rules can be brought into the online operations of underactuated manipulators. 2-DOF underactuated manipulator is taken into consideration so as to illustrate the design procedure. Computer simulation results show that the new methodology is effective in designing controllers for underactuated robot manipulators.     

Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic

Many robot controllers require not only joint position measurements but also joint velocity measurements; however, most robotic systems are only equipped with joint position measurement devices. In this paper, a new output feedback tracking control approach is developed for the robot manipulators with model uncertainty. The approach suggested herein does not require velocity measurements and employs the adaptive fuzzy logic. The adaptive fuzzy logic allows us to approximate uncertain and nonlinear robot dynamics. Only one fuzzy system is used to implement the observer-controller structure of the output feedback robot system. It is shown in a rigorous manner that all the signals in a closed loop composed of a robot, an observer, and a controller are uniformly ultimately bounded. Finally, computer simulation results on three-link robot manipulators are presented to show the results which indicate good position tracking performance and robustness against payload uncertainty and external disturbances.     

Swing-up control of a 3-DOF acrobot using an evolutionary approach

We present a control method for a 3-DOF acrobot which is a model of a gymnast on a horizontal bar with three links, two active joints, and a passive joint. This robot is a nonholonomic and underactuated system. We propose two control methods for the 3-DOF acrobot. First, swing-up control is performed by genetic programming (GP), and stabilizing control is handled by a linear quadratic regulator (LQR). GP can search widely for the optimum input torques for swing-up so that the acrobot is able to reach a near balancing point. The LQR is then switched on to stabilize the system. In the simulation results, the 3-DOF acrobot could swing up to the desired position, and the proposed method could control the acrobot effectively.     

PMSM驱动机器人的FSMC与EPCH协同控制

单独一种控制方法难以使机器人末端快速、准确地跟踪位置变化,针对这一问题,提出了模糊滑模(FSMC)信号控制与误差端口受控哈密顿(EPCH)能量控制的协同控制策略.FSMC解决了系统动态时的快速性问题,EPCH控制解决了系统稳态时的准确性问题.设计了基于误差的协同函数,利用协同函数来实现对机器人关节系统的协同控制,使机器...     

Differentially Flat Designs of Underactuated Open-Chain Planar Robots

A fully actuated system can execute any joint trajectory. However, if the system is underactuated, not all joint trajectories are attainable. For such systems, it is difficult to characterize attainable joint trajectories analytically. Numerical methods are generally used to characterize these. This paper investigates the property of differential flatness for underactuated planar open-chain robots and studies dependence on inertia distribution within the system. It is shown that certain choices of inertia distributions make an underactuated open-chain planar robot with revolute joints feedback linearizable, i.e., also differentially flat. Once this property is established, trajectory between any two points in the state space can be planned, and a controller can be developed to correct for errors. To demonstrate the proposed methodology in hardware, experiments with an underactuated 3-DOF planar robot are also presented.      

Control of three degrees-of-freedom underactuated manipulator using fuzzy based switching

A novel concept for designing a fuzzy logic-based switching controller to control underactuated manipulators is presented. The proposed controller employs elemental controllers, which are designed in advance. Parameters of both antecedent and consequent parts of a fuzzy indexer are optimized by using evolutionary computation. Design parameters of the fuzzy indexer are encoded into chromosomes, i.e., the shapes of the Gaussian membership functions and corresponding switching laws of the consequent part are evolved to minimize the angular position errors. Then, these trained fuzzy rules can be brought into the online operation of underactuated manipulators. Simulation results show that the new methodology is effective in designing controllers for underactuated robot manipulators.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003