Distributed Force/Position Consensus Tracking of Networked Robotic Manipulators

In this paper, we address the tracking problem of distributed force/position for networked robotic manipulators in the presence of dynamic uncertainties. The end-effectors of the manipulators are in contact with flat compliant environment with uncertain stiffness and distance. The control objective is that the robotic followers track the convex hull spanned by the leaders under directed graphs. We propose a distributed adaptive force control scheme with an adaptive force observer to achieve the asymptotic force synchronization in constrained space, which also maintains a cascaded closed-loop structure separating the system into kinematic module and dynamic module. A decentralized stiffness updating law is also proposed to deal with the environment uncertainties. The convergence of tracking errors of force and position is proved using Lyapunov stability theory and input-output stability analysis tool. Finally, simulations are performed to show effectiveness of the theoretical approach.      

机器人位置/力控制系统的稳定性

本文通过一个简单的两自由度机器人,分析了 Raibert 和 Craig 提出的位置/力混合控制器的不稳定性问题,提出了力微分反馈控制和在力控制方向引入位置反馈这两种克服不稳定性的方法;在此基础上,对一般机器人提出了一种有效的位置/力控制结构。大量的仿真研究显示了该控制结构的有效性,并给出了关于力控制器设计的一些重要结论.     

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。     

Independent Hybrid Force/Motion Control of Constrained Six-Degrees-of-Freedom Manipulators

Controlling the dynamics of a constrained manipulator includesposition tracking as well as stabilization of the contact wrench.In this paper we derive a control scheme, that makes it possible to treat position and force control independently.The approach is based on a mass-orthogonal splitting of the space of joint torques, allowing independent actuation and therefore independent specification of control laws. An appropriate definition of the reference wrenchmakes it possible to achieve independent stability of the position and force loop.     

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.     

Adaptive Control For Robotic Manipulators Executing Multilateral Constrained Task

This paper presents a model‐based adaptive control in task coordinates for robotic manipulators executing multilateral constrained tasks The controller works based on the concept of orthogonality between force and motion in the subspaces derived from the constraints. The control gains are independently adjustable in each subspace. The friction force, depending on the contact force, is compensated adaptively. Asymptotic convergence for both force and motion tracking errors is guaranteed by the Lyapunov‐Like Lemma. Experimental results obtained using a 3 D.O.F. robot are given.     

两机械手进行物体交接时的控制问题

为增大机械手的工作空间,本文提出一种新方法——物体交接,即一个机械手操作一物体一段时间之后,交给另一机械手操作。文中研究了物体交接的工作空间,对物体交接任务进行分解,给出了其实现方案,并对一种简单情况进行了研究。仿真结果说明控制方案是十分有效的.     

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.     

机械臂的位置与力的混合控制方法

本文研究关于机械臂的位置与力的混合控制方法.为了实现混合控制,首先应用一对被称为"任务规范投影算子"建立了机械臂混合控制的动态方程.在此基础上,提出了两种控制器的设计方法,一种是计算力矩方法控制器,另一种是动态补偿变结构控制器.后者不但具有更好的鲁棒性,并且可以分别调整运动与约束力的跟踪精度.     

Multi-Input Second-Order Sliding-Mode Hybrid Control of Constrained Manipulators

This paper deals withthe hybrid position/force control of constrainedmanipulators subjected to uncertainties. A solution is proposedthat is based on sliding-mode control theory, which proved tobe highly effective in counteracting uncertainties for some classesof nonlinear systems. Specific problems involved in this techniqueare chattering elimination and the algebraic coupling betweenconstraint forces and possibly discontinuous control signals.Both the problems are addressed in this paper by exploiting therobustness properties of a second-order sliding-mode controlalgorithm. This algorithm, recently proposed by the authors forsolving the single-input hybrid control problem, is generalizedin this paper to deal with the class of multi-input differentialalgebraic systems describing the behaviour of constrained mechanicalsystems.     

接触作业型飞行机械臂系统的力/位置混合控制

针对飞行机械臂系统移动接触作业问题,使用了一个力/位置混合控制框架,用以控制飞行器系统持续可靠地接触外部环境同时保持一定大小的接触力,并实现在接触过程中的期望轨迹跟踪.首先将作业空间分成2个子空间——约束空间和自由空间,并分别进行力控制和位置控制.对于力控制问题,证明闭环无人机系统是一个类弹簧-质量-阻尼系统,然后在约束子空间中设计逆动力学控制器来实现接触力控制.自由飞行空间中的运动控制依靠轨迹规划和位置控制器来实现.最后,开发了基于六旋翼飞行机器人的单自由度飞行机械臂系统,在飞行状态下进行接触墙面并跟踪倾斜直线轨迹的实验.结果显示本文所使用方法能够保证在平稳移动的同时控制期望的接触力.     

A Robust Adaptive Terminal Sliding Mode Control for Rigid Robotic Manipulators

In this paper, a robust adaptive terminal sliding mode controller is developed for n-link rigid robotic manipulators with uncertain dynamics. An MIMO terminal sliding mode is defined for the error dynamics of a closed loop robot control system, and an adaptive mechanism is introduced to estimate the unknown parameters of the upper bounds of system uncertainties in the Lyapunov sense. The estimates are then used as controller parameters so that the effects of uncertain dynamics can be eliminated and a finite time error convergence in the terminal sliding mode can be guaranteed. Also, a useful bounded property of the derivative of the inertial matrix is explored, the convergence rate of the terminal sliding variable vector is investigated, and an experiment using a five bar robotic manipulator is carried out in support of the proposed control scheme.     

柔性机器人的动力学建模及其控制*

本文首先综述了近年来在柔性机器人动力学建模方面所取得的进展，着重介绍了目前较常见的几种建模方法和模型，同时对柔性机器人的控制问题进行了评述，指出了今后研究的方向。     

受限机器人神经形态的变结构位置/力控制

本文基于Ｊｅａｎ和Ｆｕ（１９９３）建立的受限机器人模型的降型阶形式，利用变结构系统理论，设计了具有未知动态的受限机器人轨道／力追踪控制，提出的学习方法仅仅利用了机器人动态模型的一般结构，不需要其精确信息，计算迅速，易于实现，仿真结果验证了提出的方法的有效性。     

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.     

基于正反馈的机器人位置控制

本文提出了一种简单、精确的机器人位置控制算法，适用于快速运动并具轻微阻尼的机器人手臂，该算法采用正位置反馈策略，仅需位置传感器监测机器人手臂的关节角度以提供稳定的位置控制。最后采用两关节机器人进行了实验研究，实验结果表明了该算法的有效性。     

基于视觉／力觉的机器人协同缝制系统

针对服装制造行业中缝制过程自动化程度较低的问题,基于视觉、力觉信息设计搭建了一种机器人与缝制设备协同工作的智能缝制系统,实现了多种多边织物的自动化缝制。采用基于拐点检测的织物特征提取方法,实现机器人缝制线迹规划;在此基础上基于力／位混合控制策略,实现缝制过程中机器人与缝纫机的协同作业,保证缝制质量。最后测试了不同转速下机器人单边缝制效果以及多边织物边缘整体缝制效果。实验结果表明,设计的机器人缝制系统可以实现不同转速下双机协同缝制,缝制线迹到面料边缘距离误差小于2mm,针距误差小于0.5mm,线迹总长度误差小于1.6cm。     

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.     

机械手自适应模糊控制器设计

本文提出了一种自适应模糊控制器用于机械手轨迹跟踪控制,该控制器通过对训练数据的聚类分析提取典型数据送入神经网络学习,得到的控制规则更加适用,在线控制时可以自动调整神经网络的结构以及隶属函数的参数。仿真实验表明该控制器能够对机械手实时控制,而且精度较高。     

基于一阶不确定项估计律的机械臂鲁棒控制研究

针对多自由度机械臂控制系统的模型参数误差、关节摩擦力以及外部输入扰动等不确定项,设计了一类一阶误差估计律;结合基于机构动力学名义模型的输入输出反馈线性化控制算法,对六自由度刚性机械臂的时变轨迹跟踪控制进行了研究,理论上证明了设计的鲁棒控制器是全局渐进稳定的.仿真结果表明该控制策略对系统的各类不确定项具有很好的鲁棒性,能够实现高精度的轨迹跟踪控制.