Force Control Of Robot Manipulators Research Articles

On the robustness of force estimation methods for robot manipulators: An experimental study

Force control of robot manipulators has been extensively studied for the last decades. Whether a direct or an indirect approach is pursued, it is always desirable to know the contact forces/torques, which are usually attained through force sensors. However, there are a variety of reasons for which it may not be desirable to employ them. For instance, they are expensive and not free of noise, and for some applications, they might just be too big to be a practical solution. Following these reasons, there have been many efforts to develop estimation techniques. Some of the main challenges are the need of exact robot models as well as position, velocity, and even acceleration measurements. In this work, a compilation of some of the most employed approaches developed in the last two decades is presented, along with the design of a novel force estimation algorithm. The proposed method is a modification of the well-known Generalized Momentum approach, with the advantages of finite-time convergence and improved performance. A comparative analysis is carried out to elucidate which of the methods delivers a better performance based on two key assumptions presented at the experimental implementation: 1) the robot model is accurate, and 2) the estimated forces/torques should be employed in a control scheme without a previous closed-loop stability analysis. Both assumptions are meant to test the robustness of the different approaches since the former is not realistic, while the latter is not advisable because no separation principle is valid for nonlinear systems. However, from a practical point of view, it is interesting to substitute force measurements with no further analysis. The experimental outcomes show closed-loop stability in all cases.

Adaptive impedance control of robot manipulators based on Q-learning and disturbance observer

ABSTRACTIn this paper, an adaptive impedance control combined with disturbance observer (DOB) is developed for a general class of uncertain robot manipulators in discrete time. The impedance control is applied to realize the interaction force control of robot manipulators in unknown, time-varying environments. The optimal reference trajectory is produced by impedance control, and the impedance parameters are achieved using Q-learning technique, which is implemented based on trajectory tracking errors. The position control with DOB of robot manipulators is implemented to track the virtual desired trajectory, and the DOB is designed to compensate for unknown compounded disturbance function by bounding both tracking error inputs and compounded disturbance inputs in a permitted control region, of which the compounded disturbance function is taken into account of all uncertain terms and external disturbances. The appropriate DOB parameters are selected applying linear matrix inequalities (LMIs) method. Both the impedance control and the bounded DOB control can well guarantee semiglobal uniform boundness of the closed-loop robot systems based on Lyapunov analysis and Schur complement theory. Simulation results are performed to test and verify effectiveness of the investigated combining adaptive impedance control with DOB.

Robotic Time-Varying Force Tracking in Position-Based Impedance Control

This paper presents a unified control framework for both set-point and time-varying force control of robot manipulator by introducing an improved position-based impedance control (IPBIC). In order to essentially achieve accurate force control, especially time-varying force tracking, a new target impedance function compensated by a force controller is presented. The essence of the improved method in realizing time-varying force tracking, as well as the coupled stability of the manipulator–environment system is investigated. To further improve the force control performance, the Newton-type iterative learning control (ILC) is introduced upon the closed-loop system. A case study on a two-link robot model demonstrates the effectiveness of this method.

Impedance control of robots using voltage control strategy

Impedance control provides a unified solution for the position and force control of robot manipulators. The dynamic behavior of a robotic system in response to environment is prescribed by an impedance model formed as Thevenin model. This model is certain and linear while the robot manipulator is highly nonlinear, coupled, and uncertain. Therefore, impedance control must overcome nonlinearity, coupling, and uncertainty to convert the robotic system to the impedance model. To overcome these problems, this paper presents a novel impedance control for electrically driven robots, which is free from the manipulator dynamics. The novelty of this paper is the use of voltage control strategy to develop the impedance control. Compared with the commonly used impedance control, which is based on the torque control strategy, it is computationally simpler, more efficient, and robust. The mathematical verification and simulation results show the effectiveness of the control method.

Vision-based neural network control for constrained robots with constraint uncertainty

Research on hybrid position and force control of robot manipulators has assumed that the structure of constraint surface is known exactly. However, in many force control applications of robot, the exact model of the constraint surface cannot be obtained. In the presence of the constraint uncertainty, it is difficult to analyse the stability of the force control system. A vision-based neural network controller is proposed for robots with uncertain kinematics, dynamics and constraint surface. The proposed adaptive neural network controller does not require the exact model and structure of the constraint surface as assumed in the literature. It is shown that stability can be achieved with the uncertainties. Simulation results are presented to illustrate the performance of the proposed controller.

Fuzzy force control of constrained robot manipulators based on impedance model in an unknown environment

To precisely implement the force control of robot manipulators in an unknown environment, a control strategy based on fuzzy prediction of the reference trajectory in the impedance model is developed. The force tracking experiments are executed in an open-architecture control system with different tracking velocities, different desired forces, different contact stiffnesses and different surface figurations. The corresponding force control results are compared and analyzed. The influences of unknown parameters of the environment on the contact force are analyzed based on experimental data, and the tunings of predictive scale factors are illustrated. The experimental results show that the desired trajectory in the impedance model is predicted exactly and rapidly in the cases that the contact surface is unknown, the contact stiffness changes, and the fuzzy force control algorithm has high adaptability to the unknown environment.

604 ロボットによる力制御のための能動作業台 : 高精度な力制御の実現(OS9-1,オーガナイズドセッション:9 ロボット技術とメカトロ制御技術)

604 ロボットによる力制御のための能動作業台 : 高精度な力制御の実現(OS9-1,オーガナイズドセッション:9 ロボット技術とメカトロ制御技術)

603 ロボットによる力制御のための能動作業台 : 小型部品のバフ研磨作業への応用(OS9-1,オーガナイズドセッション:9 ロボット技術とメカトロ制御技術)

603 ロボットによる力制御のための能動作業台 : 小型部品のバフ研磨作業への応用(OS9-1,オーガナイズドセッション:9 ロボット技術とメカトロ制御技術)

619 ロボットによる力制御のための能動作業台(OS4-4 産業応用ロボメカ技術,オーガナイズドセッション4-II ロボメカシステムと要素技術)

619 ロボットによる力制御のための能動作業台(OS4-4 産業応用ロボメカ技術,オーガナイズドセッション4-II ロボメカシステムと要素技術)

ロボットの力制御のための三次元能動作業台 : 力センサフィードバック制御の適用(OS4-2 産業用メカトロニクス技術)

ロボットの力制御のための三次元能動作業台 : 力センサフィードバック制御の適用(OS4-2 産業用メカトロニクス技術)

605 ロボットによる力制御のための三次元能動作業台

605 ロボットによる力制御のための三次元能動作業台

611 ロボットの力制御のための能動作業台 : 小型鋳物部品のバフ仕上げへの応用

611 ロボットの力制御のための能動作業台 : 小型鋳物部品のバフ仕上げへの応用

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.

Behavioural Modules in Force Control of Robotic Manipulators

A behaviour-based architecture for the design of robot manipulator control in force mediated motions has been implemented. Its performance has been measured over a number of tasks to investigate the applicability of the approach. It has been found to offer a possible alternative to traditional control theory approaches in situations that do not lend themselves to an analytical approach. The proposed architecture offers a low cost means of implementing such control at an appropriate layer of abstraction for a non-specialist end user albeit at reduced accuracy and speed due to the limitations of the underlying external force control scheme.

Development of an Active Worktable and Its Application to Force Control of Robot Manipulators

An active worktable, which can be applied to force control tasks of commercial robot manipulators, has been designed and built. The active worktable has several degrees of freedom and accommodates its position/force in accordance with the motion of a robot manipulator. A stiffness control method and an impedance control method are implemented in the active worktable to achieve compliant motion. Several experiments were carried out to confirm basic effectiveness of the active worktable.

Fuzzy Predictive Algorithms Applied to Force Control of Robotic Manipulators

Abstract This paper proposes a combination of classical impedance controller with a fuzzy predictive algorithm. This control strategy allows for the inclusion of a nonlinear environment in the control design in a straightforward way, improving the global force control performance. In order to reduce the oscillations of the optimized reference position, a fuzzy scaling machine is included in the force control strategy. The performance of the force control scheme is illustrated for a two degree-of-freedom robot. Simulation results obtained with the fuzzy control scheme reveal an accurate force tracking performance considering non-rigid environments.

309 ロボットによる力制御のための能動作業台 : バフ仕上げ作業への応用(O.S.8-2 マニピュレータ・移動ロボット)(オーガナイズドセッション8 : 産業応用をめざすメカトロニクス技術)

309 ロボットによる力制御のための能動作業台 : バフ仕上げ作業への応用(O.S.8-2 マニピュレータ・移動ロボット)(オーガナイズドセッション8 : 産業応用をめざすメカトロニクス技術)

Sliding mode with adaptive estimation force control of robot manipulators interacting with an unknown passive environment

In this paper, a force control algorithm for robot manipulators is introduced, where the dynamics of non-rigid environment interacting with the robot is assumed unknown. The controller design is based on the combination of sliding mode control techniques and the adaptive estimation theory, so the introduced controller compensates the structured or unstructured uncertainty of the environment. The main source of feedback information is received from a wrist force sensor. The designed controller includes additional absorption terms in order to minimise end-point velocity error and to suppress the impact effects at the beginning of the force application.

Robot Manipulator Force Control Using Fuzzy-Neuro. Fuzzy Selection of Fuzzy-Neuro Controllers According to Environment Properties.

Force control is one of the most important and fundamental tasks of robot manipulators. In order to realize precise contact tasks with an nuknown environment, robot controllers have to adapt themselves to the unknown environment. Recently, fuzzy reasoning and/or neural networks are expected to play an important role in force control of robot manipulator. Human knowledge can be reflected in control rules by using fuzzy control method, and learning/adaptation ability can be obtained by applying neural networks to robot controllers. In this paper, an effective control policy for robot contact tasks with an unknown environment is proposed using fuzzy-neuro techniques. In this control policy, a neural network is applied to classify the unknown environment based on its dynamic response of the environment and then select the suitable fuzzy neural force controller. The selected fuzzy neural force controller is able to realize the desired contact force precisely using its on-line adaptation ability. Furthermore, the fuzzy selection of the controller is introduced for force control with the environment whose suitable fuzzy neural force controller is not prepared. The effectiveness of the proposed method is evaluated by experiment with a 2DOF planar robot manipulator.

Neural network impedance force control of robot manipulator

The performance of an impedance controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and environment stiffness. The purpose of this paper is to improve the controller robustness by applying the neural network (NN) technique to compensate for the uncertainties in the robot model. NN control techniques are applied to two impedance control methods: torque-based and position-based impedance control, which are distinguished by the way of the impedance functions being implemented. A novel error signal is proposed for the NN training. In addition, a trajectory modification algorithm is developed to determine the reference trajectory when the environment stiffness is unknown. The robustness analysis of this algorithm to force sensor noise and inaccurate environment position measurement is also presented. The performances of the two NN impedance control schemes are compared by computer simulations. Simulation results based on a three-degrees-of-freedom robot show that highly robust position/force tracking can be achieved in the presence of large uncertainties and force sensor noise.