仿生假手抓握力控制策略

为了使仿生假手完成各种精细作业,提出一种抓握力控制策略.在自由空间和约束空间中分别使用基于位置的阻抗控制和力跟踪阻抗控制.在过渡过程中使用模糊观测器切换控制模式.两种控制模式采用同一个基于位置的阻抗控制器,在约束空间向阻抗控制器中引入参考力,以满足约束空间的抓握力控制要求.这种方法可以使关节在自由空间和约束空间中分别实现良好的轨迹跟踪和力矩跟踪,在过渡过程中实现控制模式的可靠切换和系统的稳定过渡.提出一种自适应滑模摩擦力补偿方法,利用终端滑模思想设计了滑模函数,使得系统跟踪误差在有限时间内收敛,避免了传统线性滑模面状态跟踪误差无法在有限时间内收敛至0的问题.根据指数形式摩擦力的特点,利用终端滑模控制思想获得包含摩擦力参数估计的滑模控制律,并基于李亚普诺夫稳定性定理推导了估计参数的在线自适应律.对该抓握力控制策略在HIT假手上进行了抓取实验,实验结果证明了控制策略的有效性.     

基于变刚度自适应导纳机制的机械臂恒力控制

工业机械臂在诸如打磨抛光等接触式作业任务中对环境刚度信息存在一定的依赖性, 未知环境刚度信息将严重影响机器人的力位控制精度, 使得作业效果难以得到保证. 为解决环境信息不足或未知情况下的力/位置精确控制问题, 本文首先提出了一种新的自适应环境刚度在线估计方法, 针对时变的环境刚度进行实时估计, 由此预测生成后继的机械臂参考轨迹点, 随后提出了一种根据力跟踪误差实时调整末端工具手刚度系数的变刚度导纳恒力控制方法, 并结合李雅普诺夫稳定性理论给出了整体控制律的收敛性证明. 针对刚柔两种末端工具手和多种不同的曲面工件开展了实验研究, 并与传统PID控制方法和传统导纳控制方法进行了对比, 其结果表明本文所提出的复合控制方法可在不同工况条件下实现机器人运动过程中接触力的快速柔顺调节, 并获得4.55%以内的最优力控误差效果, 证明了本文所提出方法的有效性与可行性.     

Adaptive hybrid force/position control of robot manipulators using an adaptive force estimator in the presence of parametric uncertainty

This study is devoted to sensorless adaptive force/position control of robot manipulators using a position-based adaptive force estimator (AFE) and a force-based adaptive environment compliance estimator. Unlike the other sensorless method in force control that uses disturbance observer and needs an accurate model of the manipulator, in this method, the unknown parameters of the robot can be estimated along with the force control. Even more, the environment compliance can be estimated simultaneously to achieve tracking force control. In fact, this study deals with three challenging problems: No force sensor is used, environment stiffness is unknown, and some parametric uncertainties exist in the robot model. A theorem offers control laws and updating laws for two control loops. In the inner loop, AFE estimates the exerted force, and then, the force control law in the outer loop modifies the desired trajectory of the manipulator for the adaptive tracking loop. Besides, an updating law updates the estimated compliance to provide an accurate tracking force control. Some experimental results of a PHANToM Premium robot are provided to validate the proposed scheme. In addition, some simulations are presented that verify the performance of the controller for different situations in interaction.     

Adaptive Task-Space Control of Flexible-Joint Manipulators

This paper considers the motion control and compliance control problemsfor uncertain rigid-link, flexible-joint manipulators, and presents newadaptive task-space controllers as solutions to these problems. The motioncontrol strategy is simple and computationally efficient, requires littleinformation concerning either the manipulator or actuator/transmissionmodels, and ensures uniform boundedness of all signals and arbitrarilyaccurate task-space trajectory tracking. The proposed compliant motioncontrollers include an adaptive impedance control scheme, which isappropriate for tasks in which the dynamic character of theend-effector/environment interaction must be controlled, and an adaptiveposition/force controller, which is useful for those applications thatrequire independent control of end-effector position and contact force. Thecompliance control strategies retain the simplicity and model independenceof the trajectory tracking scheme upon which they are based, and are shownto ensure uniform boundedness of all signals and arbitrarily accuraterealization of the given compliance control objectives. The capabilities ofthe proposed control strategies are illustrated through computer simulationswith a robot manipulator possessing very flexible joints.     

High Precision Constrained Grasping with Cooperative Adaptive Handcontrol

A method for high precision constrained object manoeuvering for non-redundant rigid multifinger hands is proposed. A passivity-based adaptive cooperative control scheme carries out compensation of all uncertain inertial and dynamic friction forces to guarantee asymptotic tracking of all contact forces and joint position-orientation trajectories over orthogonal force- and position-based impedance error manifolds. Optimal internal and external force trajectories are obtained to minimize the contact forces onto the constrained object while exerting a given desired contact force onto the environment. The simulation study of two robot fingers manipulating a constrained object for combined fast and slow velocity regimes shows that when the dynamic friction compensation is turned on tracking errors decrease tenfold.     

Direct adaptive impedance control of robot manipulators

This article presents an adaptive scheme for controlling the end-effector impedance of robot manipulators. The proposed control system consists of three subsystems: a simple “filter” that characterizes the desired dynamic relationship between the end-effector position error and the end-effector/environment contact force, an adaptive controller that produces the Cartesian-space control input required to provide this desired dynamic relationship, and an algorithm for mapping the Cartesian-space control input to a physically realizable joint-space control torque. The controller does not require knowledge of either the structure or the parameter values of the robot dynamics and is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme represents a general and computationally efficient approach to controlling the impedance of both nonredundant and redundant manipulators. Furthermore, the method can be applied directly to trajectory tracking in free-space motion by removing the impedance filter. Computer simulation results are given for a planar four degree-of-freedom redundant robot under adaptive impedance control. These results demonstrate that accurate end-effector impedance control and effective redundancy utilization can be achieved simultaneously by using the proposed controller.     

面向未知环境基于智能预测的模糊控制器研究

提出了一种新的面向未知环境的智能预测算法，并将此算法应用于机器人力跟踪控制中．该方法利用机械手末端与未知受限环境产生的接触轨迹，通过模糊推理智能地预测阻抗控制模型中的参考轨迹，并根据力误差变化用参考比例因子对其进行调节，以适应未知环境刚度的变化．通过对阻抗模型参数进行模糊调节减少受限运动中的力误差，提高了全局的力控制效果．仿真结果证明了此算法的有效性．     

Precise and smooth contact force control for a hybrid mobile robot used in polishing

Contact force is dominant in robotic polishing since it directly determines the material removal. However, due to the position and stiffness disturbance of mobile robotic polishing and the nonlinear contact process between the robot and workpiece, how to realize precise and smooth contact force control of the hybrid mobile polishing robot remains challenging. To solve this problem, the force tracking error is investigated, which indicates that the force overshoot mainly comes from the input step signal and the environmental disturbance causes force tracking error in stable state. Accordingly, an integrated contact force control method is proposed, which combines feedforward of the desired force and adaptive variable impedance control. The nonlinear tracking differentiator is used to smooth the input step signal of the desired force for force overshoot reduction. Through modeling of the force tracking error, the adaptive law of the damping parameter is established to compensate disturbance. After theoretical analysis and simulation verification, the polishing experiment is carried out. The improvement in force control accuracy and roughness of the polished surface proves the effectiveness of the proposed method. Sequentially, the proposed method is employed in the polishing of a 76-meter wind turbine blade. The measurement result indicates that the surface roughness after mobile robotic polishing is better than Ra1.6. The study provides a feasible approach to improve the polishing performance of the hybrid mobile polishing robot.     

A force–impedance controlled industrial robot using an active robotic auxiliary device

A strategy to improve the performance of current commercial industrial robots is presented in this paper. This strategy involves cooperation of two robotic manipulators: the robotic controlled impedance device (RCID) and a commercial industrial robot. The RCID is a small six degrees-of-freedom (DOF) high bandwidth force–impedance controlled parallel manipulator, developed at the School of Engineering of the University of Porto (Portugal). The RCID works attached in series with a position controlled commercial industrial robot. Combination of the two manipulators behaves as a single manipulator having the impedance and force control dynamic performance of the RCID, as well as the workspace and trajectory tracking bandwidth of the industrial robot. Force–impedance control of the RCID, and experimental results on typical tasks that involve end-effector contact with uncertain environments of unknown stiffness are presented.     

基于阻抗模型的下肢康复机器人交互控制系统设计

为帮助下肢功能障碍患者进行康复训练,设计了下肢康复机器人。对于该机器人的控制,采用传统系统无法柔顺控制,导致机器人运动轨迹偏离预设轨迹。针对该现象,提出了基于阻抗模型的下肢康复机器人交互控制系统设计。通过分析总体控制方案,设计系统硬件结构框图。采用L型二维力传感器,确定两个方向的人机交互力。使用绝对值编码器安装在各个关节处,其输出值作为髋关节、膝关节、踝关节电机的转动位置,增量编码器安装在电机轴上,测量值用来作为后期控制方法的输入参数。构建阻抗控制模型,能够调节机器人位置和速度,具有消除力误差功能。依据此力矩对参考运动轨迹进行设计,实时获取患者康复训练的跟踪、主动柔顺和接近状态信息。在柔顺训练实验测出人机交互力,通过实验结果知,在检测到人体主动力矩异常时,系统能够重新优化轨迹,具有良好柔顺控制效果。     

Adaptive tracking control of manipulators: Theory and experiments

This paper considers the trajectory tracking problem for uncertain robot manipulators and proposes two adaptive controllers as solutions to this problem. The first controller is derived under the assumption that the manipulator state is measurable, while the second strategy is developed for those applications in which only position measurements are available. The adaptive schemes are very general and computationally efficient since they do not require knowledge of either the mathematical model or the parameter values of the manipulator dynamics, and are implemented without calculation of the robot inverse dynamics or inverse kinematic transformation. It is shown that the control strategies ensure uniform boundedness of all signals in the presence of bounded disturbances, and that the ultimate size of the tracking errors can be made arbitrarily small. Experimental results are presented for a PUMA 560 manipulator and demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed controllers.     

面向位控机器人的力/位混合控制

本文提出了一种面向位控机器人的力/位混合控制策略．通过力反馈信息对未知约 束进行估计获得位控和力控方向,根据位控和力控方向对机器人终端的运动轨迹进行规划, 并采用阻抗力控制规律以使机器人获得较好的柔顺性．仿真试验表明,该策略具有较高的力 控制精度和表面跟踪能力．     

基于无模型自适应的外骨骼式上肢康复机器人主动交互训练控制方法

设计了一种基于无模型自适应的外骨骼式上肢康复机器人主动交互训练控制方法.在机器人与人体上肢接触面安装力传感器采集人机交互力矩信息作为量化的主动运动意图,设计了一种无模型自适应滤波算法使交互力矩变得平滑而连贯;以人机交互力矩为输入,综合考虑机器人末端点与参考轨迹的相对位置和补偿力的信息,设计了人机交互阻抗控制器,用于调节各关节的给定目标速度;设计了将无模型自适应与离散滑模趋近律相结合的速度控制器完成机器人各关节对目标速度的跟踪.仿真结果表明,该控制方法可以实现外骨骼式上肢康复机器人辅助患者完成主动交互训练的功能.通过调节人机交互阻抗控制器的相应参数,机器人可以按照患者的运动意图完成不同的主动交互训练任务,并在运动出现偏差时予以矫正.控制器在设计实现过程中不要求复杂准确的动力学建模和参数识别,并有一定的抗干扰性和通用性.     

Asymmetrical nonlinear impedance control for dual robotic machining of thin-walled workpieces

Impedance control is to provide stable tracking by regulating the impedance response of a robot. In this paper, an asymmetrical nonlinear impedance control (ANIC) is proposed for a dual robotic machining system. The symmetrical linear impedance control (SLIC) is also analyzed as a comparison study. We compared two controllers in terms of the stability and the sensitivity property of the grinding force, as well as the trajectory design. The main advantage of the ANIC is that the grinding force is robust to the environmental disturbances and the variation in thickness of workpieces. In contrast to the traditional control concept, which is devoted to compensate the nonlinear effect of the original system, our design philosophy is to increase the system robustness by introducing an artificial nonlinearity to the system. As a result, the dual robotic system acts as variable stiffness actors to adapt the variation in the thickness of workpieces. Grinding experiments are conducted in the dual robotic machining test rig for both workpieces with the uniform and varied thickness. The experimental results show that the dual robotic system with the ANIC can achieve better grinding quality.     

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.     

Application of Model Reference Adaptive Control to Industrial Robot Impedance Control

The paper deals with the application of model reference adaptive control to robot impedance control, which is actually a technique of steering the end-effector on a prescribed path and satisfying a prescribed dynamic relationship between the force and the end-effector position. Due to unknown parameters of the environment (stiffness, exact position), a model reference algorithm is proposed which differs from classical algorithms in its method of excitation. The results of the proposed procedure are illustrated by implementation on the ASEA IRb 6 industrial robot.     

Voltage-based adaptive impedance force control for a lower-limb rehabilitation robot

This paper presents a novel voltage-based adaptive impedance force control for a lower limb rehabilitation robot. The impedance parameters are adaptively regulated by a gradient descent algorithm for adjusting the human force in performing therapeutic exercises. Although the proposed control is based on voltage control strategy, it differs from the common torque control strategy. One of the advantages is that it is free from the dynamical models of the robot and patient. Compared with a torque control scheme, it is simpler, less computational, and more efficient while it considers the actuators. The control approach is verified by stability analysis. Simulation results show the efficiency of the control approach applied on a lower limb rehabilitation robot driven by an electric motor. A comparison on performing isometric exercise shows that the voltage-based adaptive impedance force control is superior to both voltage-based impedance control and torque-based impedance control.     

Robust Sliding Control of Robotic Manipulators Based on a Heuristic Modification of the Sliding Gain

A task space robust trajectory tracking control is developed for robotic manipulators. A second order linear model, which defines the desired impedance for the robot, is used to generate the reference position, velocity and acceleration trajectories under the influence of an external force. The control objective is to make the robotic manipulator’s end effector track the reference trajectories in the task space. A sliding mode based robust control is used to deal with system uncertainties and external perturbations. Thus, a sliding manifold is defined by a linear combination of the tracking errors of the system in the task space built from the difference between the real and the desired position, velocity and acceleration trajectories in comparison with previous works where the sliding manifold was defined by the desired impedance and the external force. Moreover, the ideal relay has been substituted by a relay with a dead-zone in order to fit in with the actual way in which a real computational device implements the typical sign function in sliding mode control. Furthermore, a higher level supervision algorithm is proposed in order to reduce the amplitude of the high frequency components of the output associated to an overestimation of the system uncertainty bounds. Then, the robust control law is applied to the case of a robot with parametric uncertainty and unmodeled dynamics. The closed-loop system is proved to be robustly stable with all signals bounded for all time while the control objective is fulfilled in practice. Finally, a simulation example which shows the usefulness of the proposed scheme is presented.     

Fuzzy-neuro position/force control for robotic manipulators with uncertainties

The performance of a controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and the environmental stiffness. This paper aims to improve the controller’s robustness by applying the neural network to compensate for the uncertainties of the robot model at the input trajectory level rather than at the joint torque level. A self-adaptive fuzzy controller is introduced for robotic manipulator position/force control. Simulation results based on a two-degrees of freedom robot show that highly robust position/force tracking can be achieved, despite the existence of large uncertainties in the robot model.