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.     

An adaptive impedance/force controller for robot manipulators

A solution to the adaptive control of constrained robots in the presence of uncertainty in the robot model parameters is presented. The controller design is based on a singular systems model representation and fixed controller design. The adaptive control law consists of the computed torque controller plus the introduction of the parameter estimates and an additional compensation through an extra signal. Some properties of the reduced form robot model are presented and exploited to prove the asymptotic tracking properties of the adaptive controller. Also, the inclusion of the impedance control objective allows the accommodation of tangential forces that may appear in the constrained task     

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.     

Further results on adaptive iterative learning control of robot manipulators

Based on a combination of a PD controller and a switching type two-parameter compensation force, an iterative learning controller with a projection-free adaptive algorithm is presented in this paper for repetitive control of uncertain robot manipulators. The adaptive iterative learning controller is designed without any a priori knowledge of robot parameters under certain properties on the dynamics of robot manipulators with revolute joints only. This new adaptive algorithm uses a combined time-domain and iteration-domain adaptation law allowing to guarantee the boundedness of the tracking error and the control input, in the sense of the infinity norm, as well as the convergence of the tracking error to zero, without any a priori knowledge of robot parameters. Simulation results are provided to illustrate the effectiveness of the learning controller.     

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.     

Decentralized adaptive coordinated control of multiple robot arms without using a force sensor

This paper presents a distributed adaptive coordinated control method for multiple robot arms grasping a common object. The cases of rigid contact and rolling contact are analyzed. In the proposed controller, the dynamic parameters of both object and robot arms are estimated adaptively. The desired motions of the robot arms are generated by an estimated object reference model. The control method requires only the measurements of the positions and velocities of the object and robot arms, but not the measurements of forces and moments at contact points. The asymptotic convergence of trajectory is proven by the Lyapunov-like Lemma. Experiments involving two robot arms handling a common object are shown.     

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.     

Desired Compensation Adaptive Robust Control of Electrical-optical Gyro-stabilized Platform with Continuous Friction Compensation Using Modified LuGre Model

Continuous friction compensation along with other modeling uncertainties is concerned in this paper, to result in a continuous control input, which is more suitable for controller implementation. To accomplish this control task, a novel continuously differentiable nonlinear friction model is synthesized by modifying the traditional piecewise continuous LuGre model, then a desired compensation version of the adaptive robust controller is proposed for precise tracking control of electrical-optical gyro-stabilized platform systems. As a result, the adaptive compensation and the regressor in the proposed controller will depend on the desired trajectory and on-line parameter estimates only. Hence, the effect of measurement noise can be reduced and then high control performance can be expected. Furthermore, the proposed controller theoretically guarantees an asymptotic output tracking performance even in the presence of modeling uncertainties. Extensively comparative experimental results are obtained to verify the effectiveness of the proposed control strategy.

     

轮子纵向打滑条件下的移动机器人自适应跟踪控制

针对纵向滑动参数未知的轮式移动机器人的轨迹跟踪问题,提出一种自适应跟踪控制策略.利用两个未知参数来描述移动机器人左右轮的纵向打滑程度,建立了产生纵向滑动的差分驱动轮式移动机器人的运动学模型;设计了补偿纵向滑动的自适应非线性反馈控制律;应用 Lyapunov 稳定性理论与 Barbalat 定理证明了闭环系统的稳定性;同时,提出了一种由极点配置方法在线调整控制器增益的方法.仿真结果验证了所提出控制方法的有效性.     

Fuzzy sliding-mode control with rule adaptation for nonlinear systems

Abstract: A fuzzy sliding-mode control with rule adaptation design approach with decoupling method is proposed. It provides a simple way to achieve asymptotic stability by a decoupling method for a class of uncertain nonlinear systems. The adaptive fuzzy sliding-mode control system is composed of a fuzzy controller and a compensation controller. The fuzzy controller is the main rule regulation controller, which is used to approximate an ideal computational controller. The compensation controller is designed to compensate for the difference between the ideal computational controller and the adaptive fuzzy controller. Fuzzy regulation is used as an approximator to identify the uncertainty. The simulation results for two cart–pole systems and a ball–beam system are presented to demonstrate the effectiveness and robustness of the method. In addition, the experimental results for a tunnelling robot manipulator are given to demonstrate the effectiveness of the system.     

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.     

Robust Recurrent Neural Network Control of Biped Robot

In this paper, a recurrent neural network (RNN) control scheme is proposed for a biped robot trajectory tracking system. An adaptive online training algorithm is optimized to improve the transient response of the network via so-called conic sector theorem. Furthermore, L ₂-stability of weight estimation error of RNN is guaranteed such that the robustness of the controller is ensured in the presence of uncertainties. In consideration of practical applications, the algorithm is developed in the discrete-time domain. Simulations for a seven-link robot model are presented to justify the advantage of the proposed approach. We give comparisons between the standard PD control and the proposed RNN compensation method.     

An Adaptive Regulator of Robotic Manipulators in the Task Space

This note addresses the problem of position control of robotic manipulators both nonredundant and redundant in the task space. A computationally simple class of task space regulators consisting of a transpose adaptive Jacobian controller plus an adaptive term estimating generalized gravity forces is proposed. The Lyapunov stability theory is used to derive the control scheme. The conditions on controller gains ensuring asymptotic stability are obtained herein in a form of simple inequalities including some information extracted from both robot kinematic and dynamic equations. The performance of the proposed control strategy is illustrated through computer simulations for a direct-drive arm of a SCARA type redundant manipulator with the three revolute kinematic pairs operating in a two-dimensional task space.     

未知参数多变量线性系统自适应模糊广义预测控制

对未知参数多变量线性系统提出了自适应模糊广义预测控制方法.该方法直接用模糊逻辑系统组成的向量设计广义预测控制器,并基于广义误差向量估计值对控制器中的未知向量和广义误差估计值中的未知矩阵进行白适应调整.该方法不但能保证闭环系统所有信号有界,而且可使广义误差向量收敛到原点的一个邻域内.     

Decentralized adaptive control of robot manipulators

A decentralized adaptive control scheme is proposed for the trajectory tracking of a general n-degree-of-freedom robot manipulator. The robot is considered as a set of decoupled second-order systems with disturbances. The controller consists of feedforward from the desired trajectory based on the “inverse system” of the model, PID feedback from the actual trajectory, and auxiliary input for the compensation of the neglected terms in modeling in each subsystem. The gain is derived in diagonal matrix form, and is adjusted by the model reference adaptive control theory based on the Lyapunov's direct method. The result is high accuracy in path tracking despite the high speed, load change, and sudden torque disturbances. Numerical simulations on.a planar two-link robot manipulator are presented to show the performance under various practical considerations.     

Variable stiffness control for SEAs in rehabilitation training

ABSTRACT

Series Elastic Actuator (SEA) with both security and high performance is used extensively for rehabilitation robots with physical interaction. Human joints applied for motion therapy show variable stiffness properties during the process of rehabilitation training. When using robot to do motion therapy, impedance control is one of the most popular methods for rehabilitation works. However, impedance control with constant stiffness usually produces rigidity in the body due to natural changes of muscle tension. It may seriously restrict the achievement of excellent training effect and may even cause harm to patients. In this study, a novel real-time parallel variable stiffness control method is proposed based on cascade impedance controller. First, an SEA joint is analyzed and the limit factor of the impedance frequency is discussed. Subsequently, cascade impedance controller scheme with stiffness adjustment regulator is utilized to achieve the stiffness and the passivity of the controller is proved. Based on the scheme, a novel stiffness self-adjustment algorithm is presented which can regulate the stiffness by impedance approximation. Finally, simulation and experimental results are provided to validate the stiffness adjustment method during the rehabilitation process.     

Positioning control of an underwater robot with tilting thrusters via decomposition of thrust vector

Positioning control of an underwater robot is a challenging problem due to the high disturbances of ocean flow. To overcome the high disturbance, a new underwater robot with tilting thrusters was proposed previously, which can compensate for disturbance by focusing the thrusting force in the direction of the disturbance. However, the tilting motion of the thrusters makes the system nonlinear, and the limited tilting speed sometimes makes the robot unstable. Therefore, an optimized controller is necessary. A new positioning controller is proposed for this robot using a vector decomposition method. Based on the dynamic model, the nonlinear force input term of the tilting thrusters is decomposed in the horizontal and vertical directions. Based on the decomposition, the solution is determined by a pseudo-inverse and null-space solution. Using the characteristics of the decomposed input matrix, the final solution can be found by solving a simple second-order algebraic equation to overcome the limitations of the tilting speed. The positioning was simulated to validate the proposed controller by comparing the results with a switching-based controller. Tracking results are also presented. In future work, a high-level control strategy will be developed to take advantage of the tilting thrusters by focusing the forcing direction toward the disturbance with a limited stability margin.

     

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.     

Application of a hybrid controller to a mobile robot

This paper presents the application of a hybrid controller to the optimization of the movement of a mobile robot. Through hybrid controller processes, the optimal angle and velocity of a robot moving in a work space was determined. More effective movement resulted from these hybrid controller processes. The experimental scenarios involved a five-versus-five soccer game and a MATLAB simulation, where the proposed system dynamically assigned the robot to the target position. The hybrid controller was able to choose a better position according to the circumstances encountered. The hybrid controller that is proposed includes a support vector machine and a fuzzy logic controller. We used the method of generalized predictive control to predict the target position, and the support vector machine to determine the optimal angle and velocity required for the mobile robot to reach the goal. First, we used the generalized predictive control to predict the target position. Then, the support vector machine is used to classify the angle that must be followed by the mobile robot to reach the goal. Next, a fuzzy logic controller is designed to determine the velocity of the left and right wheels of the mobile robot. Thus generated, the velocity was optimized according to the measures obtained by the support vector machine. Finally, based on the optimal velocity of robot, the output membership function was modified. Consequently, the proposed hybrid controller allowed the robot to reach the goal quickly and effectively.     

Lyapunov-based control design for multiple robots handling a common object

In this article, we address the problem of controlling multiple robots manipulating a rigid object cooperatively. First we propose and prove a few fundamental properties of the multirobot dynamical system. These properties are then exploited to design aset point regulation controller. The proposed controller takes into account the dynamics of both the object and the manipulators. This controller enables us to control the position of the object and the internal forces acting on the object. An adaptive version of the proposed controller is then introduced. The adaptive controller is able to account for the uncertainty in the mass of the load while ensuring the asymptotic convergence of the load position and the internal forces to their desired values.