Force Control of Robotic Manipulators Using a Fuzzy Predictive Approach

This paper proposes a force control strategy for robotic manipulators considering a non-rigid environment described by a nonlinear model. This approach uses a fuzzy predictive algorithm to generate, in an optimal way, the reference or virtual position to the classical impedance controller in order to apply a desired force profile on the environment. The main advantage of this control strategy is the possibility of including a nonlinear model of the environment in the controller design in a straightforward way, improving the global force control performance, especially in non-rigid environments. Moreover, in order to reduce the oscillations on the optimized reference position a fuzzy scaling machine is included on the force control strategy. The performance of the force control scheme is illustrated for a two degree-of-freedom PUMA 560 robot, which end-effector is forced to move along a flat surface located on the vertical plane. The simulation results obtained with the fuzzy control scheme reveal significant improvement in the force tracking performance, when compared to the impedance control with force tracking in non-rigid environments.     

软体机械臂水下自适应鲁棒视觉伺服

水下仿生软体机器人在水底环境勘测, 水下生物观测等方面具有极高的应用价值. 为进一步提升仿章鱼臂软体机器人在特殊水下环境中控制效果, 提出一种自适应鲁棒视觉伺服控制方法, 实现其在干扰无标定环境中的高精度镇定控制. 基于水底动力学模型, 设计保证动力学稳定的控制器; 针对柔性材料离线标定过程繁琐、成本高, 提出材料参数自适应估计算法; 针对水下特殊工作条件, 设计自适应鲁棒视觉伺服控制器, 实现折射效应的在线补偿, 并通过自适应未知环境干扰上界, 避免先验环境信息的求解. 所提算法在软体机器人样机中验证其镇定控制性能, 为仿生软体机器人的实际应用提供理论基础.     

机械臂的动态混合控制

本文研究当机械臂的终端受有约束时的控制问题,其中心内容是给出“任务规范投影算子”的概念,利用它首先将机械臂的动态方程解耦为两组方程,它们分别描述了运动与约束力,在此基础上给出了机械臂的控制律,使闭环系统跟踪期望的速度与约束力。     

一种工业机器手的自适应阻抗控制方法

提出一种基于任务空间的直接自适应阻抗方法，它不要求辨识机器手动态模型结构和参数，不需要计算机器手的运动学逆变换，因此，避免了基于机器手模型线性参数辨识的控制方法的缺点。     

Robust Hybrid Control of Constrained Robot Manipulators via Decomposed Equations

Basing on a constraint Jacobian induced orthogonal decomposition of the task space and by requiring the force controller to be orthogonal to the constraint manifold, the dynamics of the constrained robots under hybrid control is decomposed into a set of two equations. One describes the motion of robots moving on the constraint manifold, while the other relates the constraint force with the hybrid controller. This decomposition does not require the solution of the constraint equation in partition form. In this setting, the hybrid control of constrained robots can be essentially reduced to robust stabilization of uncertain nonlinear systems whose uncertainties do not satisfy the matching condition. A continuous version of the sliding-mode controller (from Khalil [12]) is employed to design a position controller. The force controller is designed as a proportional force error feedback of high gain type. The coordination of the position controller and the force controller is shown to achieve ultimately bounded position and force tracking with tunable accuracy. Moreover, an estimate of the domain of attraction is provided for the motion on the constraint manifold. Simulation for a planar two-link robot constraining on an ellipse is given to show the effectiveness of a hybrid controller. In addition, the friction effect, viewed as external disturbance to the system, is also examined through simulations.     

Robotic Control with Partial Visual Information

We consider a robotic setting and a class of control tasks that rely on partial visual information. These tasks are difficult in the sense that at every given moment, the available information is insufficient for the control task. This implies that the image Jacobian, which relates the image space and the control space, is no longer of full rank. However, the amount of information collected throughout the control process is still large and thus seems sufficient for carrying out the task. Such situations commonly arise when the object is frequently occluded from one of the cameras in a stereo pair or when only one moving camera is available. We propose a generic control rule for such tasks and characterize the conditions required for the success of the task. The analysis is based on the observation that mathematically the behavior of such systems is related to a class of row-action optimization algorithms which are special cases of POCS (Projection On Convex Sets) algorithms. In the second part of the paper we focus on one particular task from this class: position and orientation control with a single rotating camera. We show that this task can be carried out, in principle, for any camera rotation and suggest efficient control and camera moving strategies. We substantiate our claims by simulations and experiments. Interestingly, it seems that the advisable control law is not consistent with simple intuition.     

基于迭代学习的机械手操作空间力/位置混合控制算法

基于对常规机械手操作空间力/位置混合控制算法的简单回顾,及对该算法所遇到困难的分析,提出了一种基于迭代学习的机械手操作空间力/位置混合控制算法,来改善机械手同高刚度环境接触时,机械手力/位置混合控制的动态控制性能．给出了学习算法的收敛条件及其证明.实验表明该算法具有快速的收敛性,能达到很高的力/位置动态控制精度.     

Decentralized PD and Robust Nonlinear Control for Robot Manipulators

A decentralized PD and robust nonlinear feedback law for robot motioncontrol is proposed. The control system structure is based on thegeneralized tracking error proposed by Slotine and Li. Using this systemstructure, a simple and comprehensive result on the local stabilityconditions of PD control is obtained. A decentralized robust nonlinearfeedback term is then added to it to improves the performance of trackingerrors from local convergence to global convergence. Since the approachkeeps the simplicity of the independent joint controller structure it can beeasily implemented in most robot systems without hardware alteration.     

Force Sensing Using Kalman Filtering Techniques for Robot Compliant Motion Control

Robot motion can be classified into free and contact motion. In practical tasks, however, the motion may transit from free motion to contact motion and vice versa. In such tasks, a position controller is designed in free motion. A compensator is then added in the force feedback loop to help the system reach the desired target impedance when the end-effector is in contact with the environment. To obtain accurate contact force, a Kalman filter is used to extract contact force from the wrist force sensor signal which contains inertial force of the end-effector also.     

一种基于混合视觉伺服的切换控制方法

为解决目标远离摄像机视野问题,本文提出了一种基于混合视觉伺服的切换控制方法,根据目标在图像平面的位置,通过在两种具有不同特性的控制策略之间进行切换完成视觉伺服任务.采用的混合视觉伺服方法实现了平动和转动自由度的解耦,当目标位于图像平面中心区域时,采用控制策略使转动自由度误差指数级减小;当目标位于边界区域时,切换到另一种控制策略,使目标重新回到中心区域,通过切换控制最终完成伺服任务.仿真实验验证了提出的基于混合视觉伺服切换控制方法的有效性.     

On the Robust Nonlinear Motion Position and Force Control of Flexible Joints Robot Manipulators

The design of a robust nonlinear position and force controller for a flexible joints robot manipulator interacting with a rigid environment is presented. The controller is designed using the concept of feedback linearization, sliding mode techniques, and LQE estimation methodologies. It is shown that the nonlinear robot manipulator model is feedback linearizable. A robust performance of the proposed control approach is achieved by accounting for the system parameters uncertainties in the derivation of the nonlinear control law. An upper bound of the error introduced by parametric uncertainties in the system is computed. Then, the feedback linearizing control law is modified by adding a switching action to compensate the errors and to guarantee the achievement of the desired tracking performance. The relationship between the minimum achievable boundary layer thickness and the parametric uncertainties is derived. The proposed controller is tested using an experimental flexible joints robot manipulator, and the results demonstrate its potential benefits in reducing the number of sensors required and the complexity of the design. This is achieved by eliminating the need for nonlinear observers. A robust performance is obtained with minimum control effort by taking into account the effect of system parameter uncertainties and measurement noise.     

一种机器人自适应阻抗控制算法

本文针对参数未知及负载不确定下的机器人运动控制问题，提出了一种形式非常简洁的自适应阻抗控制算法，它能使机器人系统跟踪目标阻抗并保证跟踪误差的渐近稳定性及机器人与外界整体系统的稳定性，本文还就无直接力反馈控制方法进行了讨论。     

Integrating Optical Force Sensing with Visual Servoing for Microassembly

For microassembly tasks uncertainty exists at many levels. Single static sensing configurations are therefore unable to provide feedback with the necessary range and resolution for accomplishing many desired tasks. In this paper we present experimental results that investigate the integration of two disparate sensing modalities, force and vision, for sensor-based microassembly. By integrating these sensing modes, we are able to provide feedback in a task-oriented frame of reference over a broad range of motion with an extremely high precision. An optical microscope is used to provide visual feedback down to micron resolutions, while an optical beam deflection technique (based on a modified atomic force microscope) is used to provide nanonewton level force feedback or nanometric level position feedback. Visually servoed motion at speeds of up to 2 mm/s with a repeatability of 0.17 m are achieved with vision alone. The optical beam deflection sensor complements the visual feedback by providing positional feedback with a repeatability of a few nanometers. Based on the principles of optical beam deflection, this is equivalent to force measurements on the order of a nanonewton. The value of integrating these two disparate sensing modalities is demonstrated during controlled micropart impact experiments. These results demonstrate micropart approach velocities of 80 m/s with impact forces of 9 nN and final contact forces of 2 nN. Within our microassembly system this level of performance cannot be achieved using either sensing modality alone. This research will aid in the development of complex hybrid MEMS devices in two ways; by enabling the microassembly of more complex MEMS prototypes; and in the development of automatic assembly machines for assembling and packaging future MEMS devices that require increasingly complex assembly strategies.     

A Robust Control Law with Estimated Perturbation Compensation for Robot Manipulators

By considering the dynamic response of a robot manipulator as characterized by the sliding function, a technique is proposed to estimate the perturbation in the robot control system. Perturbation compensation is then incorporated in the design of a robust control law to cancel the effects of system parametric uncertainties and external disturbances. A normalized power rate component is introduced to replace the discontinuous control that is usually associated with variable structure system. The suggested robust control law ensures that the robot control system reaches an user specified neighbourhood of the sliding manifold in finite time and with prescribed transient behaviour. Explicit estimates of the bounds on modelling errors and external disturbances are not required while signal measurement uncertainties can be accommodated. Furthermore, using the equivalent control concept, a very simple expression is derived to estimate the system perturbation signal. Detailed computer simulation results are presented to demonstrate the effectiveness of the proposed control law.     

一种受限机械手的自适应力/位置控制方法*

对于受限机械臂,本文提出了一种自适应的力/位置控制方法。其实现是基于给出的新的降阶动力学模型,在反馈信号中引入力的累积误差信号,利用降阶模型的本身特性从而达到自适应力/位置控制的目的。给出的自适应律是通过跟踪误差信号来调节的。仿真结果证实了本方法的正确性。     

考虑柔性关节的机械臂自适应运动控制策略研究

具有柔性关节的轻型机械臂因其自重轻、响应迅速、操作灵活等优点,取得了广泛应用;针对具有柔性关节的机械臂系统的关节空间轨迹跟踪控制系统动力学参数不精确的问题,提出一种结合滑模变结构设计的自适应控制器算法;通过自适应控制的思想对系统动力学参数进行在线辨识,并采用Lyapunov方法证明了闭环系统的稳定性;仿真结果表明,该控制策略保证了机械臂系统对期望轨迹的快速跟踪,具有良好的跟踪精度,系统具有稳定性。     

A Dynamic-compensation Approach to Impedance Control of Robot Manipulators

This paper presents an impedance–control strategy with dynamic compensation for interaction control of robot manipulators. The proposed impedance controller has been developed considering that the equilibrium point of the closed-loop system, composed by the combination of the controller and the full nonlinear robot dynamics is, locally, asymptotically stable in agreement with Lyapunov’s direct method. The performance of the proposed controller is verified through simulation and experimental results obtained from the implementation of an interaction task involving a two degree-of-freedom, direct-drive robot.     

一种新的双环结构机器人无标定自抗扰视觉伺服控制方法

在研究基于自抗扰控制器的机器人无标定视觉伺服方法的基础上,提出了一种新的双环结构机器人无标定自抗扰视觉伺服控制方法．内环采用Kalman滤波算法进行图像雅可比矩阵的在线辨识,可较好地逼近真实模型;外环采用自抗扰控制器,利用非线性观测器实时估计系统相对于当前估计模型的总扰动,并在控制中加以动态补偿．针对六自由度工业机器人进行了二维运动目标的跟踪实验,实验结果表明了该方法的可行性和有效性．     

Robust Saturated PI Joint Velocity Control for Robot Manipulators

It is well known that many industrial manipulators use an embedded linear proportional‐integral (PI) joint velocity controller to guarantee motion control through proper velocity commands. However, although this control scheme has been very successful in practice, not much attention has been paid to designing new PI velocity control structures. The problem of analyzing a saturated PI velocity joint velocity controller is addressed in this paper. By using the theory of singularly perturbed systems, the closed‐loop system is studied. The robot dynamics assumed in this paper take into account bounded time–varying disturbances which may include the friction at the joints. An experimental study in a planar two degrees‐of‐freedom direct‐drive robot is also presented, confirming the advantage of the new saturated PI joint velocity controller.     

一种拟人空间机械臂视觉伺服图像处理研究

针对四自由度串并混联拟人空间机械臂本体,构建了基于运动控制卡模式的机器人软件和硬件系统。采用基于位置的控制结构,利用所求得的机械臂逆运动学方程,设计了由图像反馈和末端运动组成的视觉伺服控制系统。提出了一种基于SURF特征的静态目标识别算法,算法首先对目标图像提取SURF特征,并利用欧氏距离实现模板图像与目标图像特征点匹配,然后计算已匹配特征点的质心来获得目标的位置信息,最终实现了稳定的伺服定位。实验结果证明了系统的可靠性,并且证明了四自由度串并混联机械臂本体在实际运动的精确性和稳定性。