Adaptive fuzzy control of mechanicalbehavior for a two degree-of-freedomrobotic manipulator

Active compliance control of robotic manipulators is useful in making robots perform precision assembly operations. The essential requirement here is mechanical isotropy of the robot end-point. In this paper the problem of how to achieve this kind of mechanical behaviour is considered from aspects of impedance control and fuzzy set theory. The new fuzzy–impedance control law, which is suitable for real-time applications, is proposed for a two degree-of-freedom (2-d.o.f.) robotic manipulator. According to simulation results, the proposed control law can provide approximately isotropic behaviour of the robot end-point in the whole workspace.     

Learning Control of Robot Manipulators in Task Space

Two important properties of industrial tasks performed by robot manipulators, namely, periodicity (i.e., repetitive nature) of the task and the need for the task to be performed by the end‐effector, motivated this work. Not being able to utilize the robot manipulator dynamics due to uncertainties complicated the control design. In a seemingly novel departure from the existing works in the literature, the tracking problem is formulated in the task space and the control input torque is aimed to decrease the task space tracking error directly without making use of inverse kinematics at the position level. A repetitive learning controller is designed which “learns” the overall uncertainties in the robot manipulator dynamics. The stability of the closed‐loop system and asymptotic end‐effector tracking of a periodic desired trajectory are guaranteed via Lyapunov based analysis methods. Experiments performed on an in‐house developed robot manipulator are presented to illustrate the performance and viability of the proposed controller.     

Global finite-time inverse tracking control of robot manipulators

This paper addresses the global finite-time tracking of robot manipulators. By replacing with the nonlinear exponential-like errors, the commonly used inverse dynamics control for robot manipulators is modified to produce global finite-time tracking. Using this method, the controlled robotic system is transformed into a nonlinear and decoupled one, and thus the tracking performance is very convenient to quantify. A Lyapunov-like argument along with finite-time stability analysis is employed to prove global finite-time stability. Simulations performed on a two degree-of-freedom (DOF) manipulator are provided to illustrate the effectiveness and the improved performance of the formulated algorithm.     

Robot path planning in a constrained workspace by using optimal control techniques

Robot manipulators are programmable mechanical systems designed to execute a great variety of tasks in a repetitive way. In industrial environment, while productivity increases, cost reduction associated with robotic operation and maintenance can be obtained as a result of decreasing the values of dynamic quantities such as torque and jerk, with respect to a specific task. Furthermore, this procedure allows the execution of various tasks that require maximum system performance. By including obstacle avoidance ability to the robot skills, it is possible to improve the robot versatility, i.e., the robot can be used in a variety of operating conditions. In the present contribution, a study concerning the dynamic characteristics of serial robot manipulators is presented. An optimization strategy that considers the obstacle avoidance ability together with the dynamic performance associated with the movement of the robot is proposed. It results an optimal path planning strategy for a serial manipulator over time varying constraints in the robot workspace. This is achieved by using multicriteria optimization methods and optimal control techniques. Numerical simulation results illustrate the interest of the proposed methodology and the present techniques can be useful for the design of robot controllers. Commemorative contribution.     

Upper Bounding Estimation for Robustness to the Parameter Uncertainty with Trigonometric Function in Trajectory Control of Robot Arms

In this paper, a new robust control law is considered for controlling robot manipulators subjected to uncertainties. The control law is derived as a result of analytical solution from the Lyapunov function, thus stability of the uncertain system is guaranteed. Apart from previous studies, uncertainty bound and adaptation gain matrix are updated in time with the estimation law to control the system properly and uncertainty bound is determined using a trigonometric function of robot kinematics, inertia parameters and tracking error while adaptation gain matrix is determined using a trigonometric function of robot kinematics and tracking error. Application to a two-link robotic manipulator is presented and numerical simulations are included.     

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.     

Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier

We design a regulation-triggered adaptive controller for robot manipulators to efficiently estimate unknown parameters and to achieve asymptotic stability in the presence of coupled uncertainties.Robot manipulators are widely used in telemanipulation systems where they are subject to model and environmental uncertainties.Using conventional control algorithms on such systems can cause not only poor control performance,but also expensive computational costs and catastrophic instabilities.Therefore,system uncertainties need to be estimated through designing a computationally efficient adaptive control law.We focus on robot manipulators as an example of a highly nonlinear system.As a case study,a 2-DOF manipulator subject to four parametric uncertainties is investigated.First,the dynamic equations of the manipulator are derived,and the corresponding regressor matrix is constructed for the unknown parameters.For a general nonlinear system,a theorem is presented to guarantee the asymptotic stability of the system and the convergence of parameters'estimations.Finally,simulation results are discussed for a two-link manipulator,and the performance of the proposed scheme is thoroughly evaluated.     

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．     

机械手的模糊逆模型鲁棒控制

提出一种基于模糊聚类和滑动模控制的模糊逆模型控制方法,并将其应用于动力学方程未知的机械手轨迹控制.首先,采用C均值聚类算法构造两关节机械手的高木-关野(T-S)模糊模型,并由此构造模糊系统的逆模型.然后,在提出的模糊逆模型控制结构中,离散时间滑动模控制和时延控制(TDC)用于补偿模糊建模误差和外扰动,保证系统的全局稳定性并改进其动态和稳态性能.系统的稳定性和轨迹误差的收敛性可以通过稳定性定理来证明.最后,以两关节机械手的轨迹跟随控制为例,揭示了该设计方法的控制性能.     

An adaptive neural network switching control approach of robotic manipulators for trajectory tracking

In this paper, an adaptive neural network (NN) switching control strategy is proposed for the trajectory tracking problem of robotic manipulators. The proposed system comprises an adaptive switching neural controller and the associated robust compensation control law. Based on the Lyapunov stability theorem and average dwell-time approach, it is shown that the proposed control scheme can guarantee tracking performance of the robotic manipulators system, in the sense that all variables of the closed-loop system are bounded and the effect due to the external disturbance and approximate error of radical basis function (RBF) NNs on the tracking error can be converged to zero in an infinite time. Finally, simulation results on a two-link robotic manipulator show the feasibility and validity of the proposed control scheme.     

Simulation of Industrial Manipulators Based on the UDU T Decomposition of Inertia Matrix

The UDU ^T – U and D are respectively the upper triangular and diagonal matrices – decomposition of the generalized inertia matrix of an n-link serial manipulator, introduced elsewhere, is used here for the simulation of industrial manipulators which are mainly of serial type. The decomposition is based on the application of the Gaussian elimination rules to the recursive expressions of the elements of the inertia matrix that are obtained using the Decoupled Natural Orthogonal Complement matrices. The decomposition resulted in an efficient order n, i.e., O(n), recursive forward dynamics algorithm that calculates the joint accelerations. These accelerations are then integrated numerically to perform simulation. Using this methodology, a computer algorithm for the simulation of any n degrees of freedom (DOF) industrial manipulator comprising of revolute and/or prismatic joints is developed. As illustrations, simulation results of three manipulators, namely, a three-DOF planar manipulator, and the six-DOF Stanford arm and PUMA robot, are reported in this paper.     

考虑柔性关节的机械臂自适应运动控制策略研究

具有柔性关节的轻型机械臂因其自重轻、响应迅速、操作灵活等优点,取得了广泛应用;针对具有柔性关节的机械臂系统的关节空间轨迹跟踪控制系统动力学参数不精确的问题,提出一种结合滑模变结构设计的自适应控制器算法;通过自适应控制的思想对系统动力学参数进行在线辨识,并采用Lyapunov方法证明了闭环系统的稳定性;仿真结果表明,该控制策略保证了机械臂系统对期望轨迹的快速跟踪,具有良好的跟踪精度,系统具有稳定性。     

Integrated Environment for Modelling, Simulation and Control Design for Robotic Manipulators

In this paper an integrated environment for the design of robotic controllers implemented on a PC is described. It is based on the Planar Manipulators Toolbox for dynamic simulation of redundant planar manipulators. The tools are fully integrated in the MATLAB/SIMULINK and hence, a lot of standard tools are available for the analysis and control design. Using the real-time simulation it is possible to apply the developed controllers to a real robot manipulator, which can be included in the system via corresponding interfaces, without any additional coding. The main advantage is the flexibility in fast prototyping of different algorithms in the field of control of robotic systems, especially for redundant manipulators.     

Logarithmic based robust approach to parametric uncertainty for control of robot manipulators

In this paper, a new robust control law for controlling robot manipulators with parameter uncertainty is presented. A controller is designed based on the Lyapunov function and the control law that guarantees the system stability is derived as a result of analytical solution. Apart from previous studies, uncertainty bound and adaptation gain matrix are determined using the estimation law to control the system properly, and so this estimation law is developed as a logarithmic function depending on robot kinematics inertia parameters and tracking error. An application of the proposed control input to a two‐link robot manipulator is presented and numerical simulations are included. Copyright © 2005 John Wiley & Sons, Ltd.     

Inverse Kinematics of Binary Manipulators Using a Continuum Model

Binary actuators have only two discrete states, both of which are stable without feedback. As a result, manipulators with binary actuators have a finite number of states. The major benefits of binary actuation are that extensive feedback control is not required, reliability and task repeatability are very high, and two-state actuators are generally very inexpensive, resulting in low cost robotic mechanisms. These manipulators have great potential for use in both the manufacturing and service sectors, where the cost of high performance robotic manipulators is often difficult to justify. The most difficult challenge with a binary manipulator is to achieve relatively continuous end-effector trajectories given the discrete nature of binary actuation. Since the number of configurations attainable by binary manipulators grows exponentially in the number of actuated degrees of freedom, calculation of inverse kinematics by direct enumeration of joint states and calculation of forward kinematics is not feasible in the highly actuated case. This paper presents an efficient method for performing binary manipulator inverse kinematics and trajectory planning based on having the binary manipulator shape adhere closely to a time-varying curve. In this way the configuration of the arm does not exhibit drastic changes as the end effector follows a discrete trajectory.     

Self-calibrated robotic manipulator force observer

In the robotic manipulation context, end-effector contact forces may be difficult to measure mainly due to the tool dynamic interferences such as the inertial forces. In this paper, a whole methodology is proposed to estimate these forces. The new approach is based on a sensor fusion technique that integrates the information of a wrist force sensor, of a 3D accelerometer placed at the robot tool and the joint position sensors measurements. The proposed methodology not only offers a suitable estimator in terms of response and filtering, but also presents a self-calibrating feature that allows an easy integration into any industrial setup. To experimentally validate the performance of the proposed methodology, two different industrial manipulators were used: an ABB robot and a Stäubli robot, both with open control system architectures. An impedance control scheme was used as force/position control law to demonstrate the need and results of the proposed calibration result.     

Industrial Robot Navigation and Obstacle Avoidance Employing Fuzzy Logic

This paper proposes a novel conceptual approach based on fuzzy logic to solve the local navigation and obstacle avoidance problem for industrial 3-dof robotic manipulators. The proposed system is divided into separate fuzzy units, which control individually each manipulator link. The fuzzy rule-base of each unit combines a repelling influence, which is related to the distance between the manipulator and the nearby obstacles, with the attracting influence produced by the angular difference, between the actual and the final manipulator configuration, to generate a new actuating command for each link. It can be considered as an on-line local navigation method for the generation of instantaneous collision-free trajectories. The strategy has been successfully applied to manipulators in different simulated workspace environments providing collision-free paths. Some of the simulation results obtained are included.     

Position synchronised control of multiple robotic manipulators based on integral sliding mode

In this study, a new position synchronised control algorithm is developed for multiple robotic manipulator systems. In the merit of system synchronisation and integral sliding mode control, the proposed approach can stabilise position tracking of each robotic manipulator while coordinating its motion with the other manipulators. With the integral sliding mode, the proposed approach has insensitiveness against the lumped system uncertainty within the entire process of operation. Further, a perturbation estimator is proposed to reduce chattering effect. The corresponding stability analysis is presented to lay a foundation for theoretical understanding to the underlying issues as well as safely operating real systems. An illustrative example is bench tested to validate the effectiveness of the proposed approach.     

Adaptive synchronised tracking control for multiple robotic manipulators with uncertain kinematics and dynamics

In this study, a new adaptive synchronised tracking control approach is developed for the operation of multiple robotic manipulators in the presence of uncertain kinematics and dynamics. In terms of the system synchronisation and adaptive control, the proposed approach can stabilise position tracking of each robotic manipulator while coordinating its motion with the other robotic manipulators. On the other hand, the developed approach can cope with kinematic and dynamic uncertainties. The corresponding stability analysis is presented to lay a foundation for theoretical understanding of the underlying issues as well as an assurance for safely operating real systems. Illustrative examples are bench tested to validate the effectiveness of the proposed approach. In addition, to face the challenging issues, this study provides an exemplary showcase with effectively to integrate several cross boundary theoretical results to formulate an interdisciplinary solution.     

A design of digital adaptive control systems for space robot manipulators using a transpose of the generalized Jacobian matrix

We propose a digital control method for space robot manipulators using the transpose of the generalized Jacobian matrix. The method, however, is developed on the supposition that all the physical parameters of the robot manipulator are known. Therefore, if the end-effector of the manipulator captures an object whose mass is unknown, the stability of the control system cannot be maintained because the physical parameters are changed. This article presents the adaptive control version.This work was presented, in part, at the 9th International Symposium on Artificial Life and Robotics, Oita, Japan, January 28–30, 2004