Robust motion control with the consideration algorithm of joint torque saturation for a redundant manipulator

As each joint actuator of a robot manipulator has a limit value of torque, the motion control system should consider the torque saturation. In order to consider the torque saturation in a transient state, this paper proposes a new redundant motion control system using the autonomous consideration algorithm on torque saturation. A Jacobian matrix of a redundant robot manipulator can select the optimal one considering its motion energy in the steady state. When the motion control system carries out fast motion and quick disturbance suppression, a high joint torque is required in a transient state. In the experimental results, under the condition of having a large payload torque and a fast motion reference, the proposed redundant manipulator control realizes the quick robot motion robustly and smoothly.     

New inverse kinematic algorithms for redundant robots

New inverse kinematic algorithms for generating redundant robot joint trajectories are proposed. The algorithms utilize the kinematic redundancy to improve robot motion performance (in joint space or Cartesian space) as specified by certain objective functions. The algorithms are based on the extension of the existing “joint-space command generator” technique in which a null space vector is introduced which optimizes a specific objective function along the joint trajectories. In this article, the algorithms for generating the joint position and velocity (PV) trajectories are extensively developed. The case for joint position, velocity, and acceleration (PVA) generation is also addressed. Application of the algorithms to a four-link revolute planar robot manipulator is demonstrated through simulation. Several motion performance criteria are considered and their results analyzed.     

空间机器人目标捕获过程中的载体姿态扰动优化

针对自由飘浮空间机器人在捕获目标的过程中会对其载体姿态产生扰动的问题,提出了一种新的笛卡儿轨迹参数化方法.建立了反映载体姿态变化的日标函数,该函数既可以限制机器人关节角的运动范围,也可以避免动力学奇异的影响.利用遗传算法进行目标函数的优化,有效降低了空间机器人末端执行器在跟踪笛卡儿轨迹时对载体姿态的影响.仿真结果验证了...     

Force-guided motions of a 6-d.o.f. industrial robot with a joint space approach

This article deals with the interaction between humans and industrial robots, more specifically with the new design and implementation of an algorithm for force-guided motions of a 6-d.o.f. robot. It may be used to comfortably teach positions without using any teaching pendant or for some assistance tasks. For this purpose, from readings of the force/torque sensor mounted in the robot wrist, the gravity forces and torques first have to be eliminated. To control the robot in joint space, it is then convenient to transform the external force and torque values from Cartesian space into joint space using the manipulator transposed Jacobian. This is why with the present approach the Jacobian matrix of the robot used was calculated. Now, from the computed joint torques, suitable position commands of the robot arm can be generated to obtain the desired behavior. A suggestion for this desired behavior is also included in this article. It is based on the impedance control approach in joint space. The proposed algorithm was implemented with the standard Stäubli RX90B industrial robot.     

基于PMSM驱动的柔性关节空间机械臂轨迹跟踪控制方法

针对目前柔性关节空间机械臂轨迹跟踪控制方法忽略了不同重力影响下的机械臂驱动力变化,导致柔性关节空间机械臂轨迹跟踪控制效果较差的问题,提出了基于PMSM驱动的柔性关节空间机械臂轨迹跟踪控制方法。基于构建PMSM驱动数学模型,采用PMSM的矢量控制方法,分析驱动力矩矢量。根据驱动力矩矢量分析结果,分析不同重力环境下有、无摩擦时的驱动力矩。构建柔性关节模型,分析其在不同重力环境下遇到的重力释放问题,使用自适应反演滑膜控制方法,设计控制率,保证机械臂能够按照既定的方向运动,使机械臂具有鲁棒性。根据柔性关节空间机械臂动力学特性,分析不同重力环境下基于PMSM驱动力矩,确定重力项是随之发生改变的。设计控制器,构建动力学模型,确保空间阶段能够最大限度跟踪运动轨迹。实验结果表明,所提方法X轴、Y轴的末端跟踪结果均与实际运动轨迹一致,误差为0。关节控制力矩在时间为3s时,出现了最大为0.5N.m的误差,说明所提方法的跟踪控制效果较好。     

Real-time implementation of a robust adaptive controller for arobotic manipulator based on digital signal processors

Presents an approach to the design and real-time implementation of an adaptive controller for a robotic manipulator based on digital signal processors. The Texas Instruments DSP (TMS320C31) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for robotic manipulators. In the proposed scheme, adaptation laws are derived from the direct model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feedforward and feedback controller and PI-type time-varying auxiliary control elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for an industrial robot with four joints in the joint space and Cartesian space     

基于模糊控制系统的机械臂自适应控制算法设计

针对现有机械臂控制算法,在轨迹控制和精度补偿方面存在的不足,设计了一种基于模糊补偿系统的自适应控制算法。先在笛卡尔空间内分析了机械臂的空间动力学运动过程,并得出机械臂运动中的最优力矩值,构建模糊控制规则并设定模糊子集;对经典模糊理论进行优化,引入可变论域思维在机械臂运动过程中,系统会实时反馈末端执行器行动轨迹,并实施动态化补偿;基于自适应算法对可变论域模糊控制器进行二次优化,修正模糊规则并校正模型的控制量参数,提升和改善整个机械臂系统的控制精度。实验结果显示,模糊补充自适应控制算法在多关节和多连杆机械臂的角度控制和位移控制精度方面有较大的优势,同时各关节和连杆的运动相应时间仅为0.27s和0.20s。     

Singularity robust path planning for real time base attitude adjustment of free-floating space robot

This paper presents a singularity robust path planning for space manipulator to achieve base (satellite) attitude adjustment and end-effector task. The base attitude adjustment by the movement of manipulator will save propellant compared with conventional attitude control system. A task-priority reaction null-space control method is applied to achieve the primary task of adjusting attitude and secondary task of accomplishing end-effector task. Furthermore, the algorithm singularity is eliminated in the proposed algorithm compared with conventional reaction null-space algorithm. And the singular value filtering decomposition is introduced to dispose the dynamic singularity, the unit quaternion is also introduced to overcome representation singularity. Hence, a singularity robust path planning algorithm of space robot for base attitude adjustment is derived. A real time simulation system of the space robot under Linux/RTAI (realtime application interface) is developed to verify and test the feasibility and reliability of the method. The experimental results demonstrate the feasibility of online base attitude adjustment of space robot by the proposed algorithm.     

DSP/FPGA-based Controller Architecture for Flexible Joint Robot with Enhanced Impedance Performance

Some practical issues associated with enhancing the Cartesian impedance performance of flexible joint manipulator are investigated. A digital signal processing/field programmable gate array (DSP/FPGA) structure is proposed to realize the singular perturbation based impedance controller. To increase the bandwidth of torque control and minimize the joint torque ripple, boundary layer system and field-oriented control (FOC) are fully implemented in a FPGA of each joint. The kernel of the hardware system is a peripheral component interface (PCI)-based high speed floating-point DSP for the Cartesian level control, and FPGA for high speed (200 us cycle time) multipoint low-voltage differential signaling (M-LVDS) serial data bus communication between robot Cartesian level and joint level. Experimental results with a four-degree-of-freedom flexible-joint manipulator under constrained-motion task, demonstrate that the controller architecture can enhance the robot impedance performance effectively.     

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.     

Operating robot manipulators through kinematic singularities using a continuously sliding mode control

Planning the motion of end-effectors of robot manipulators can be carried out more directly in the Cartesian space compared to the joint space. Yet, Cartesian paths may include singular configurations where conventional control schemes suffer from excessive joint velocities and loss of tracking accuracy. The difficulties arise because the Jacobian matrix that is used to establish a linear relation between the velocities in the task and joint spaces loses rank at singularities. The problem can be resolved by using a local second-order approximation of robot kinematics for the joint velocities, which is called Resolved Motion Quadratic Rate Control. In this article, we present a control strategy based on this approach and a recently developed variable structure control scheme. The controller receives Cartesian inputs whenever the manipulator is outside the singular domain. Otherwise, it uses resolved motion quadratic rate control to compute the required joint inputs. Numerical simulation is performed to show that the proposed control scheme provides accurate tracking of the desired motion without inducing excessive control activity when operating robot manipulators through singular configurations. © 1994 John Wiley & Sons, Inc.     

基于连杆力矩传感器动态补偿的机器人灵巧手笛卡儿阻抗控制

为了对连杆空间力矩传感器进行动态补偿,提出了适用于求取串联机器人任意连杆中任意一点处所受的内力和内力矩的算法.该算法采用连杆假想截断原理利用牛顿-欧拉方程推导而出.推导过程综合考虑了串联机器人是否处于静态以及末端是否受外力作用的情况,以及串联机器人的关节是否是回转关节的情况.然后利用该算法计算动态补偿值,构建了基于连杆力矩传感器动态补偿的笛卡儿阻抗控制器.最后在HIT/DLR Hand II五指灵巧手上进行了实验验证.实验结果一方面验证了该算法的有效性,另一方面也验证了本文所构建的笛卡儿阻抗控制器的有效性.     

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.     

空间机器人随机故障容错规划的蜜蜂算法

本文为解决复杂的随机规划问题设计了一种基于随机模拟的混沌量子蜜蜂算法,证明了该算法的收敛 性,并分析了算法的收敛速度．分析6 自由度空间机器人系统的不确定性,采用基于微分变换法进行误差分析,建 立了随机数学规划模型．为涉及故障前后运动学与动力学约束限制的容错轨迹规划,以加权最小驱动力矩为优化性 能指标,采用混沌量子蜜蜂算法求解全部工作时间中机械臂故障前后的最优轨迹．通过降低异常关节的运动速度来 降低故障关节力矩,保证机械臂在发生故障后具有较高的操作能力．案例研究验证了该算法的有效性、稳定性及准 确性．     

Robustness analysis of a pd controller with approximate gravity compensation for robot manipulator control

Asymptotically stable robot manipulator control in both joint space and Cartesian space can be achieved by using a PD controller with gravity torque compensation. However, the stability of this class of control law has not been analyzed with the use of estimated gravity torques. The objective of this article is to present such a stability proof assuming uncertainty in the gravity estimate. The proof is carried out for the Cartesian space controller. The result is supported by computer simulation. © 1994 John Wiley & Sons, Inc.     

Collision-Free Cartesian Trajectory Generation Using Raster Scanning and Genetic Algorithms

An algorithm for Cartesian trajectory generation by redundant robots in environments with obstacles is presented. The algorithm combines a raster scanning technique, genetic algorithms and functions for interpolation in the joint coordinates space in order to approximate a desired Cartesian curve by the robot's hand tip under maximum allowed position deviation. A raster scanning technique determines a minimal set of knot points on the desired curve in order to generate a Cartesian trajectory with bounded position approximation error. Genetic algorithms are used to determine an acceptable robot configuration under obstacle avoidance constraints corresponding to a knot point. Robot motion between two successive knot points is finally achieved using well known interpolation techniques in the joint coordinates space. The proposed algorithm is analyzed and its performance is demonstrated through simulated experiments carried out on planar redundant robots.     

Cartesian path generation of robot manipulators using continuous genetic algorithms

In this paper, the authors describe a novel technique based on continuous genetic algorithms (CGAs) to solve the path generation problem for robot manipulators. We consider the following scenario: given the desired Cartesian path of the end-effector of the manipulator in a free-of-obstacles workspace, off-line smooth geometric paths in the joint space of the manipulator are obtained. The inverse kinematics problem is formulated as an optimization problem based on the concept of the minimization of the accumulative path deviation and is then solved using CGAs where smooth curves are used for representing the required geometric paths in the joint space through out the evolution process. In general, CGA uses smooth operators and avoids sharp jumps in the parameter values. This novel approach possesses several distinct advantages: first, it can be applied to any general serial manipulator with positional degrees of freedom that might not have any derived closed-form solution for its inverse kinematics. Second, to the authors’ knowledge, it is the first singularity-free path generation algorithm that can be applied at the path update rate of the manipulator. Third, extremely high accuracy can be achieved along the generated path almost similar to analytical solutions, if available. Fourth, the proposed approach can be adopted to any general serial manipulator including both nonredundant and redundant systems. Fifth, when applied on parallel computers, the real time implementation is possible due to the implicit parallel nature of genetic algorithms. The generality and efficiency of the proposed algorithm are demonstrated through simulations that include 2R and 3R planar manipulators, PUMA manipulator, and a general 6R serial manipulator.     

An algorithmic approach to coordinate transformation for robotic manipulators

Coordinate transformation is one of the most important issues in robotic manipulator control. Robot tasks are naturally specified in work space coordinates, usually a Cartesian frame, while control actions are developed on joint coordinates. Effective inverse kinematic solutions are analytical in nature; they exist only for special manipulator geometries and geometric intuition is usually required. Computational inverse kinematic algorithms have recently been proposed; they are based on general closed-loop schemes which perform the mapping of the desired Cartesian trajectory into the corresponding joint trajectory. The aim of this paper is to propose an effective computational scheme to the inverse kinematic problem for manipulators with spherical wrists. First an insight into the formulation of kinematics is given in order to detail the general scheme for this specific class of manipulators. Algorithm convergence is then ensured by means of the Lyapunov direct method. The resulting algorithm is based on the hand position and orientation vectors usually adopted to describe motion in the task space. The analysis of the computational burden is performed by taking the Stanford arm as a reference. Finally a case study is developed via numerical simulations.     

弧焊机器人焊缝跟踪神经网络控制器

介绍了一种能提高高弧焊机器人焊缝跟踪精度的神经网络控制器,通过神经网络的补偿作用,弥补了由于无法知道机器人精确模型所造成的控制上的误差,不同于机器人控制中传统的网络控制器,本文提出并应用了基于笛卡尔空间轨迹控制的机器人焊缝跟踪神经网络,大大简化了控制算法,计算机模拟及实验表明,该控制器非常适用于只的实际焊接,对于现有机器人,无须改变其控制器内部结构,即可应用该技术,与常用的机器人关节力矩控制法相比     

基于区域限定的奇异位置避免规划算法

目前人们关于奇异位形的处理研究主要包括两大类,一类是研究如何避免,一类是研究如何通过奇异点.在分析了国内外关于奇异位形的研究基础上,本文提出了基于空间区域限定的奇异位置避免算法.其核心思想就是预先对机器人运动轨迹进行规划,给出了奇异位置及邻近奇异位置的区域划分方法,从而保证在笛卡尔空间规划时能规划出一合理的插值点,同时也基于高次多项式曲线理论对关节空间规划做了优化,保证了关节和末端运动的连续性、稳定性等.通过6轴机械臂在四五六关节时的奇异为实例,运用该算法对奇异的处理做了实例分析.然后通过给定初始点和目标点的位姿等参数,定时采样数据,并利用MATLAB对规划前后获得的数据进行了图形仿真,验证了该算法的正确性和可行性.