Dynamic two arm hybrid position/force control

A useful two arm robot system will not only need to cooperatively manipulate the same object, but also need the ability for external force control. As an example, assume two robots are building a space station, which requires them to connect a structure to a partially built space station. This implies that they need to cooperatively move the object to the desired position, and then apply a force to connect it. Therefore, two arm hybrid position/force control is necessary. To accomplish this task quickly and accurately the dynamics of arm 1, arm 2, and the object must be taken into account. The external and internal forces must be clearly defined to be used in the servo control loop. There are several ways to choose the internal force: zero internal force, arbitrary force distribution, minimizing object strain energy, and minimizing the total torque. An example is shown to illustrate the trade-offs. A controller is presented which incorporates the dynamics of each arm, the dynamics of the object, and servos on the internal and external force. Experimental results show that servoing on the internal force will reduce the force error significantly.     

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.     

On the invariance of the hybrid position/force control

Recently, the noninvariance nature of the Raibert and Craig hybrid control scheme, based on the work of Mason and others, has been pointed out. In fact, on the basis of the screw theory, Lipkin and Duffy demonstrated that the selection of the position and force controlled degrees of freedom in the Raibert and Craig scheme, may give wrong results if a translation or change in unit length of the coordinate frame is performed. A general theoretical solution to this problem, called kinestatic filtering, has been given by Lipkin and Duffy. In this paper, the two approaches are summarized and discussed. First, the conditions in which the Mason filtering technique fails are determined and, second, the situations where the Lipkin and Duffy approach cannot be applied owing to degeneracy of the twist and wrench spaces, are reported. As a consequence of this analysis, a new invariant kinestatic filtering method is proposed. The method here presented is based on the original Mason approach and requires the definition of a task-dependent filter based on the knowledge of the position of the compliant frame. Examples are presented and discussed.     

考虑起止加速度的不确定机械手鲁棒控制

在机械手的点到点运动中,起始加速度和终止加速度过大都会导致较大的瞬时控制力矩,易对机械手造成损伤同时使系统不稳定。针对这个问题并考虑机械手系统的非参数不确定性,提出了合理的解决方案。首先选择了一种零起始和零终止加速度的期望轨迹曲线,基于跟踪误差设计滑模函数,同时设计PI控制器和反演控制器,最后证明了闭环系统的稳定性。利用二自由度机械手模型进行仿真实验,仿真结果证明了该方法的正确性和有效性。     

Stability and switching control design issues for a class of discrete time hybrid systems

For the class of systems considered, necessary and sufficient stabilizability conditions are unknown. However, by considering the same systems with unknown but bounded exogenous disturbances, we give finitely computable conditions, sufficient for stabilizability without disturbances, yet necessary for stabilizability with disturbances.     

Automated robotic grinding by low-powered manipulator

A new robotic grinding process has been developed for a low-powered robot system using a spring balancer as a suspension system. To manipulate a robot-arm in the vertical plane, a large actuator torque is required due to the tool weight and enormous gravity effect. But the actuators of the robot system always exhibit a limited torque capacity. This paper presents a cheap and available system for precise grinding tasks by a low-powered robot system using a suspension system. For grinding operations, to achieve position and force-tracking simultaneously, this paper presents an algorithm of the hybrid position/force-tracking scheme with respect to the dynamic behavior of a spring balancer. Material Removal Rate (MRR) is developed for materials SS400 and SUS304. Simulations and experiments have been carried out to demonstrate the feasibility of the proposed system.     

Coordination control for bilateral teleoperation with kinematics and dynamics uncertainties

The coordination control design problem for the master–slave system is addressed in this paper. In order to meet the actual work condition, we assume that the master works in a laboratory, the slave works in remote side where the environment is very complex, and the master and slave are in different sizes. Three problems are needed to be solved: system dynamics uncertainties, system kinematics uncertainties, and the asymmetric time-varying delays. The new task-space based Proporation plus damping (P+d) controller and adaptive fuzzy P+d controller are proposed for the master and the slave, respectively. By choosing proper Lyapunov functions, we have proved that the synchronization errors converge to zero asymptotically with the new controllers. The delay-dependent stability criterion is derived. With the given parameters, the proposed allowable maximal transmission delay can be computed. Finally, the simulations are performed to show the effectiveness of the proposed method.     

Model-independent position domain sliding mode control for contour tracking of robotic manipulator

In this paper, a new position domain feedback type sliding mode control (PDC-SMC) law is proposed for contour tracking control of multi-DOF (degree of freedom) nonlinear robotic manipulators focusing on the improvement of contour tracking performances. One feature of the proposed control law is its model-independent control scheme that can avoid calculation of the feedforward part in a standard SMC. The new control law takes the advantages of the high contour tracking performance of PD type feedback position domain control (PDC) and the robustness of SMC. Stability analysis is performed using the Lyapunov stability theory, and simulation studies are conducted to verify the effectiveness of the developed PDC-SMC control system. In addition, the effects of control parameters of the SMC on system performances are studied.     

Robust computationally efficient control of cooperative closed-chain manipulators with uncertain dynamics

This article presents a decentralized control scheme for the complex problem of simultaneous position and internal force control in cooperative multiple manipulator systems. The proposed controller is composed of a sliding mode control term and a force robustifying term to simultaneously control the payload's position/orientation as well as the internal forces induced in the system. This is accomplished independently of the manipulators dynamics. Unlike most controllers that do not require prior knowledge of the manipulators dynamics, the suggested controller does not use fuzzy logic inferencing and is computationally inexpensive. Using a Lyapunov stability approach, the controller is proven to be robust in the face of varying system's dynamics. The payload's position/orientation and the internal force errors are also shown to asymptotically converge to zero under such conditions.     

Force/position tracking for a robotic manipulator in compliant contact with a surface using neuro-adaptive control

The problem of force/position tracking for a robotic manipulator in compliant contact with a surface under non-parametric uncertainties is considered. In particular, structural uncertainties are assumed to characterize the compliance and surface friction models, as well as the robot dynamic model. A novel neuro-adaptive controller is proposed, that exploits the approximation capabilities of the linear in the weights neural networks, guaranteeing the uniform ultimate boundedness of force and position error with respect to arbitrarily small sets, plus the boundedness of all signals in the closed loop. Simulations highlight the approach.     

基于Matlab机械臂力控系统仿真研究

以位置控制为主的机械臂控制方法已不能满足某些复杂环境（装配、抛光、去毛刺）的应用要求,控制机械臂与环境间的接触力已成为机器人学研究的一个热点。提出一种在Matlab/SimMechanics环境下平面二自由度机械臂力控制的仿真研究方法。在平面中模拟机械臂与环境的接触面,设计振荡抑制控制器,实现机械臂与环境间接触力的控制,以及机械臂与刚性环境碰撞接触过程中冲击振荡阶段的振荡抑制,生成机械臂期望的运动轨迹。仿真结果表明,该方法可实现特定作业下机械臂与环境间接触力的控制。     

Symmetry position/force hybrid control for cooperative object transportation using multiple humanoid robots

A symmetry position/force hybrid control framework for cooperative object transportation tasks with multiple humanoid robots is proposed in this paper. In a leader-follower type cooperation, follower robots plan their biped gaits based on the forces generated at their hands after a leader robot moves. Therefore, if the leader robot moves fast (rapidly pulls or pushes the carried object), some of the follower humanoid robots may lose their balance and fall down. The symmetry type cooperation discussed in this paper solves this problem because it enables all humanoid robots to move synchronously. The proposed framework is verified by dynamic simulations.     

A hybrid receding-horizon control scheme for nonlinear systems

A hybrid receding-horizon control scheme for nonlinear discrete-time systems is proposed. Whereas a set of optimal feedback control functions is defined at the continuous level, a discrete-event controller chooses the best control action, depending on the current conditions of a plant and on possible external events. Such a two-level scheme is embedded in the structure of abstract hybrid systems, thus making it possible to prove a new asymptotic stability result for the hybrid receding-horizon control approach.     

Robust adaptive vibration control for an uncertain flexible Timoshenko robotic manipulator with input and output constraints

The problems of the constraints and the vibration suppression are investigated for the flexible Timoshenko robotic manipulator in this paper. Robust adaptive boundary control laws with the disturbance observes are designed to guarantee the convergence of the feedback flexible Timoshenko robotic manipulator system with the uncertain parameters and the states are proven to be uniform bounded. In addition, the proposed boundary controls are verified to be effectiveness by the numeral experiments.     

Mimo and siso self-tuning hybrid position/force control of robotic manipulators

This article presents a new approach for the hybrid position/force control of a manipulator by using self-tuning regulators (STR). For this purpose, the discrete-time stochastic multi-input multi-output (MIMO) and single-input single-output (SISO) models are introduced. The MIMO model's output vector has the positions and velocities of the gripper expressed in the world (xyz) coordinate system as the components. The SISO model outputs are the hybrid errors consisting of the derivatives of the position and force errors at the joints. The inputs of both models are the joint torques. The unknown parameters of those models can be calculated recursively on-line by the square-root estimation algorithm (SQR). An adaptive MIMO and SISO self-tuning type controllers are then designed by minimizing the expected value of a quadratic criterion. This performance index penalizes the deviations of the actual position and force path of the gripper from the desired values expressed in the Cartesian coordinate system. An integrating effect is also included in the performance index to remove the steady-state errors. Digital simulation results using the parameter estimation and the control algorithms are presented and the performances of those two controllers are discussed. © 1996 John Wiley & Sons, Inc.     

Position/force hybrid control system for high precision aligning of small gripper to ring object

A position/force hybrid control system based on impedance control scheme is designed to align a small gripper to a special ring object. The vision information provided by microscope vision system is used as the feedback to indicate the position relationship between the gripper and the ring object. Multiple image features of the gripper and the ring object are extracted to estimate the relative positions between them. The end-effector of the gripper is tracked using the extracted features to keep the gripper moving in the field of view. The force information from the force sensor serves as the feedback to ensure that the contact force between the gripper and the ring object is limited in a small safe range. Experimental results verify the effectiveness of the proposed control strategy.     

Position and force tracking control of rigid-link electrically-driven robots

This paper introduces a framework for the design of tracking controllers for rigid-link electrically-driven (RLED) robot manipulators operating under constrained and unconstrained conditions. We present an intuitive nonlinear control strategy that can easily be reformulated for robots performing high precision tasks. The main emphasis is placed on the development of controllers that incorporate both motion in freespace and under constrained conditions. Another novelty is the combined treatment of force control and compensation for actuator dynamics. Based on models of the robot dynamics and environmental constraints, a reduced order dynamic model is obtained for the mechanical subsystem with respect to a set of constraint variables. A design procedure for tracking controllers is then formulated for the reduced order manipulator dynamics and the DC actuator dynamics. This paper concentrates on the theoretical aspects of the problem and, hence, is based on exact knowledge of the entire system. However, we have illustrated recently in [1] that this assumption can be generously relaxed in the design of a robust controller following a similar procedure as discussed in this paper.     

Two strategies of position and force control for two industrial robots handling a single object

The simultaneous position and force control problem for two industrial robots in handling a single object is studied in this paper. Two strategies, position-position control and position-force control, are first proposed. Stability analysis is then conducted for the strategies. Both strategies result in a stable system for simple robotic models. Steady state error is also studied for the strategies. Finally, experimental results are presented to evaluate the two strategies.     

Event-driven optimization-based control of hybrid systems with integral continuous-time dynamics

In this paper we introduce a class of continuous-time hybrid dynamical systems called integral continuous-time hybrid automata (icHA) for which we propose an event-driven optimization-based control strategy. Events include both external actions applied to the system and changes of continuous dynamics (mode switches). The icHA formalism subsumes a number of hybrid dynamical systems with practical interest, e.g., linear hybrid automata. Different cost functions, including minimum-time and minimum-effort criteria, and constraints are examined in the event-driven optimal control formulation. This is translated into a finite-dimensional mixed-integer optimization problem, in which the event instants and the corresponding values of the control input are the optimization variables. As a consequence, the proposed approach has the advantage of automatically adjusting the attention of the controller to the frequency of event occurrence in the hybrid process. A receding horizon control scheme exploiting the event-based optimal control formulation is proposed as a feedback control strategy and proved to ensure either finite-time or asymptotic convergence of the closed-loop.