Predictive adaptive control of multiple robots in cooperative motion

In this paper we address the problem of controlling multiple non redundant robots manipulating a rigid object cooperatively when the parameters of the robots and the parameters of the load are uncertain. We propose a controller that takes into account the dynamics of both the load and the manipulators. The linearity of the dynamics of the robots and the load, with respect to the unknown parameters, is exploited during the derivation of the parameter's adaptation scheme. In order to design control and update laws that do not require the measurements of the joint accelerations or the load acceleration, the dynamics of both the robots and the load are filtered through a stable first order filter. Two prediction error vectors are then defined as the difference between the measured filtered dynamics and the predicted filtered dynamics of both the robots and the load. The least-squares estimation method or gradient method can be used to estimate the parameters of the multi-robot system from the prediction errors. We then develop a controller that is based on the cancellation of the nonlinearities. The proposed controller guarantees asymptotic tracking of the load trajectories and also guarantees asymptotic tracking of the internal forces trajectories.     

Dynamic control of free-floating coordinated space robots

The position and force control of coordinated robots mounted on spacecraft, manipulating objects with closed kinematic chain constraints, represents an important class of control problem. In this article, the kinematics and dynamics of free-floating coordinated space robotic system with closed kinematic constraints are developed. An approach to position and force control of free-floating coordinated space robots with closed kinematic constraints is proposed for the first time. Unlike previous coordinated space robot control methods which are for open kinematic chains, the method presented here addresses the main difficult problem of control of closed kinematic chains. The controller consists of two parts, position controller and internal force controller, which regulate, respectively, the object position and internal forces between the object and end-effectors. The stability of the closed-loop coordinated robotic system is analyzed using the error models of the object position and internal forces. It is proved that the errors in the object position and internal forces asymptotically converge to zero under the assumption of exact kinematic and dynamic models. © 1998 John Wiley & Sons, Inc.     

Adaptive neural controller for cooperative multiple robot manipulator system manipulating a single rigid object

In this article, an adaptive neural controller is developed for cooperative multiple robot manipulator system carrying and manipulating a common rigid object. In coordinated manipulation of a single object using multiple robot manipulators simultaneous control of the object motion and the internal force exerted by manipulators on the object is required. Firstly, an integrated dynamic model of the manipulators and the object is derived in terms of object position and orientation as the states of the derived model. Based on this model, a controller is proposed that achieves required trajectory tracking of the object as well as tracking of the desired internal forces arising in the system. A feedforward neural network is employed to learn the unknown dynamics of robot manipulators and the object. It is shown that the neural network can cope with the unknown nonlinearities through the adaptive learning process and requires no preliminary offline learning. The adaptive learning algorithm is derived from Lyapunov stability analysis so that both error convergence and tracking stability are guaranteed in the closed loop system. Finally, simulation studies and analysis are carried out for two three-link planar manipulators moving a circular disc on specified trajectory.     

Sliding mode cooperative motion control of dual arm manipulators

This paper presents a method for realizing cooperative control of dual-arm manipulators (RM-10A by Remotec Inc.) handling the same object in the presence of dynamic parameter uncertainties of both robots and object. When multiple robots handle the same object, both the position and the internal forces between the robots and the object should be controlled. In this paper, a sliding mode controller is derived for trajectory tracking of object position and internal forces. To show the effectiveness of the proposed controller, numerical simulations are performed for 12 axis dual-arm manipulators. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998     

Continuous shape-grinding experiment based on model-independent force/position hybrid control method with on-line spline approximation

Based on the analysis of interaction between manipulator’s hand and working object, a model representing the constrained dynamics of robot is first discussed. The constraint forces are expressed by algebraic function of states, input generalized forces, and constraint condition, and then a decoupling control method of force and position of manipulator’s hand tip is proposed. In order to give the grinding system the ability to adapt to any object shape being changed by the grinding, estimating function of the constraint condition in real time for the adaptive force/position control was added, which is indispensable for the proposed method without using force sensor. This paper explores whether the performance of the proposed controller is independent of alloy work-piece models or not. The experimental result is shown to verify the feature of the decoupling control of force and position of the tip.     

An adaptive friction compensator for global tracking in robot manipulators

A novel adaptive friction compensator based on a dynamic model recently proposed in the literature is presented in this paper. The compensator ensures global position tracking when applied to an n degree of freedom robot manipulator perturbed by friction forces with only measurements of position and velocity, and all the system parameters (robot and friction model) unknown. Instrumental for the solution of the problem is the observation that friction compensation can be recasted as a disturbance rejection problem. The control signal is then designed in two steps, first a classical adaptive robot controller that (strictly) passifies the system, and then a relay-based outer-loop that rejects the disturbance.     

Modeling and adaptive coordination control of a two-Robot system

Multiple robots are usually required in a flexible manufacturing system or a complex working environment. In particular, when an object under processing is too big or too heavy, a single robot is insufficient to handle it. Two robots are applicable in such case. This article aims to develop a complete mathematical model and an adaptive controller for two robots carrying a common load. It will be shown that the dynamic model of the two-robot system turns out to be a singular system, taking into account the object dynamics. The condition for which the system model holds is also discussed. The adaptive controller will be used to overcome uncertainties in the object dynamics and robots. The distributed forces in the robot end effectors are determined by an optimal criterion. It will be shown that the adaptive controller surpasses the conventional computed torque controller.     

Adaptive control strategies for cooperative dual-arm manipulators

The article describes three strategies for adaptive control of cooperative dual-arm robots. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through the load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the coupling effects between the arms through the load are treated as “disturbances” which are rejected by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. The controllers have simple structures and are computationally fast for on-line implementation with high sampling rates. Simulation results are given to illustrate the proposed adaptive control strategies.     

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.     

伺服电机驱动的连铸结晶器振动系统受限状态下预设性能控制

以伺服电机驱动的连铸结晶器振动位移系统为研究对象,针对系统输入和状态受限问题,考虑系统存在的参数不确定性和负载转矩扰动影响,设计一种基于观测器的预设性能自适应控制器.首先,针对系统存在的参数不确定性、负载转矩扰动等问题,基于Lyapunov函数设计变增益扩张状态观测器,在保证观测精度的同时,削弱峰值现象;其次,考虑状态和输入受限的情况,将预设性能函数与Backstepping技术相结合设计控制器,构建指令滤波器解决“计算膨胀”问题,引入动态补偿量对观测器及受限状态产生的误差进行补偿,并对所设计的控制器进行稳定性分析;最后,通过仿真对比实验验证控制器的有效性.     

Disturbance Observer-based Proportional-type Position Tracking Controller for DC Motor

This article exhibits a nonlinear proportional-type position tracking controller for DC motors, taking the parameter and load variations into account. The proposed method makes two contributions. First, a first-order disturbance observer (DOB) is devised in order to exponentially estimate the disturbances caused by parameter and load uncertainties. Secondly, a proportional-type nonlinear position tracking controller is constructed by incorporating the resulting DOB in order to ensure two useful closed-loop properties; namely, performance recovery and offset-free properties without the tracking error integral actions. The experimental result confirms the efficacy of the proposed method where a 30-W DC motor is used with an half bridge inverter.     

gripper

Grasping of objects has been a challenging task for robots. The complex grasping task can be defined as object contact control and manipulation subtasks. In this paper, object contact control subtask is defined as the ability to follow a trajectory accurately by the fingers of a gripper. The object manipulation subtask is defined in terms of maintaining a predefined applied force by the fingers on the object. A sophisticated controller is necessary since the process of grasping an object without a priori knowledge of the object's size, texture, softness, gripper, and contact dynamics is rather difficult. Moreover, the object has to be secured accurately and considerably fast without damaging it. Since the gripper, contact dynamics, and the object properties are not typically known beforehand, an adaptive critic neural network (NN)-based hybrid position/force control scheme is introduced. The feedforward action generating NN in the adaptive critic NN controller compensates the nonlinear gripper and contact dynamics. The learning of the action generating NN is performed on-line based on a critic NN output signal. The controller ensures that a three-finger gripper tracks a desired trajectory while applying desired forces on the object for manipulation. Novel NN weight tuning updates are derived for the action generating and critic NNs so that Lyapunov-based stability analysis can be shown. Simulation results demonstrate that the proposed scheme successfully allows fingers of a gripper to secure objects without the knowledge of the underlying gripper and contact dynamics of the object compared to conventional schemes.     

Adaptive control of redundant multiple robots in cooperative motion

A redundant robot has more degrees of freedom than what is needed to uniquely position the robot end-effector. In practical applications the extra degrees of freedom increase the orientation and reach of the robot. Also the load carrying capacity of a single robot can be increased by cooperative manipulation of the load by two or more robots. In this paper, we develop an adaptive control scheme for kinematically redundant multiple robots in cooperative motion.In a usual robotic task, only the end-effector position trajectory is specified. The joint position trajectory will therefore be unknown for a redundant multi-robot system and it must be selected from a self-motion manifold for a specified end-effector or load motion. In this paper, it is shown that the adaptive control of cooperative multiple redundant robots can be addressed as a reference velocity tracking problem in the joint space. A stable adaptive velocity control law is derived. This controller ensures the bounded estimation of the unknown dynamic parameters of the robots and the load, the exponential convergence to zero of the velocity tracking errors, and the boundedness of the internal forces. The individual robot joint motions are shown to be stable by decomposing the joint coordinates into two variables, one which is homeomorphic to the load coordinates, the other to the coordinates of the self-motion manifold. The dynamics on the self-motion manifold are directly shown to be related to the concept of zero-dynamics. It is shown that if the reference joint trajectory is selected to optimize a certain type of objective functions, then stable dynamics on the self-motion manifold result. The overall stability of the joint positions is established from the stability of two cascaded dynamic systems involving the two decomposed coordinates.     

High-gain adaptive position control

High-gain adaptive position control is proposed for a stiff one-mass system (1MS) and an elastic two-mass system (2MS). The control objective is (load-side) position reference tracking and disturbance rejection (of load torques and friction). Position and speed are available for feedback. Two simple high-gain adaptive position control strategies are presented and applied to a laboratory setup: an adaptive λ-tracking controller and a funnel controller. Both controllers neither estimate nor identify the plant. The λ-tracking controller achieves tracking with prescribed asymptotic accuracy: for given λ?>?0 (arbitrary small) the error approaches the interval [?λ,?λ] asymptotically. Whereas the funnel controller assures tracking with prescribed transient accuracy: the error and its derivative are bounded by prescribed positive (possibly non-increasing) functions of time. A simple proportional-integral (PI)-like extension for the 1MS, and this extension in combination with a high-pass filter for the 2MS, allow for zero tracking errors in steady-state, respectively. Oscillations in the shaft of the 2MS can be suppressed.     

Non-linear position control of cooperative hydraulic manipulators handling unknown payloads

In this paper, a non-linear stable control scheme is developed for performing a cooperative task by hydraulic manipulators. The goal is to design a controller that allows two or more hydraulic robots to coordinately regulate an object's position/orientation while maintaining specified load sharing between the manipulators as well as desired internal forces on the object. First the complete dynamic model of the whole system is described. Then, a controller is designed, augmented by an on-line updating law to eliminate the steady-state errors due to lack of knowledge about the payload. Extended Lyapunov's second method is used for stability analysis of the control system. The stability of the system is guaranteed by constructing a smooth Lyapunov function. Simulations are performed to substantiate the controller developed in this paper.     

A Generalized Vision-based Stiffness Controller for Robot Manipulators with Bounded Inputs

Generally, stiffness and impedance control schemes require knowledge of the location of any object with which a robot interacts within its workspace; therefore, the integration of a computer vision system within the control loop allows us to know the location of the robot end effector and the object (target) simultaneously. In this paper, a generalized and saturating vision-based stiffness controller with adaptive gravity compensation is presented. The proposed control algorithm is designed to regulate robot-environment interaction in task-space, where the contact force is modeled as a vector of generalized bounded spring-like forces. In order to control nonredundant robots, the proposed controller has a nonlinear proportional-derivative structure with static model-based compensation of gravitational forces, as it includes a regressor-based adaptive term. To support the proposal, the Lyapunov stability analysis of the closed-loop equilibrium vector is presented. Finally, the suitable performance of the proposed scheme was verified by numerical simulations and experimental tests.

     

参数未知的多个操作器的一种自适应控制算法

在多个操作器的内力与运动的控制中,内力控制是主要的挑战.在假设接触模型为点接触的前提下,讨论了参数未知的多个操作器内力的自适应控制.先给出多个操作器所成系统具有的一些特性;其次导出了内力误差与动力学参数间的关系;最后在条件PE(persistent-exciting)不成立的情况下,给出了一种保证内力收敛于零的复合控制.由理论证明及仿真实验可知,本文给出的控制器既使被操作的物体运动轨迹渐进跟踪期望的运动轨迹,又使作用在物体上的内力渐进跟踪期望的内力.     

冷带轧机液压伺服位置系统的鲁棒输出反馈控制

载力的干扰项视为未知输入, 构造未知输入观测器, 然后基于所构造的观测器设计鲁棒输出反馈控制器. 理论分析表明, 所提出的控制方法能够保证闭环系统是一致有界稳定的, 并具有鲁棒H1性能. 最后对某个650mm可逆冷带轧机液压伺服位置系统进行仿真研究, 结果验证了所提出方法的有效性.     

Adaptive control of Hammerstein–Wiener nonlinear systems

The Hammerstein–Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein–Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.     

改进的内模跟踪控制对随机噪声抑制的研究与仿真

对于存在随机噪声和干扰的系统,传统的内模跟踪控制是无法解决这类问题的。将自适应滤波器引入到内模控制的结构中,很好地解决了内模控制在抑制随机噪声方面的不足。针对被控对象的模型和系统性能指标,同时考虑到系统的随机噪声设计自适应滤波器,从而构建自适应控制器。通过自适应控制器和基于内模原理设计的伺服补偿器对被控对象进行跟踪控制。提出的方法综合了内模控制和自适应滤波的优点,使控制系统达到满意的跟踪控制效果,对常规谐波扰动和随机噪声都有良好的抑制作用。仿真结果表明提出的设计方法能够实现系统的无静差跟踪,并且具有良好的抗噪性和稳定性。