• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.85.1-85
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• 2002

In this paper, a control strategy of position and force is proposed based on a switching algorithm. The main focus is the control of position and force in the same direction. The switching algorithm based on a fuzzy algorithm determines the weighting value of force control. First, the force control is dominant. If the position gets closer to the desire position, the weighting value of force control is closer to zero. The proposed algorithm is shown to be satisfactory to position and force control and the weighting factor is quite successful by simulation examples.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.308-310
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• 1994

Position control for robot manipulator may not suffice when any contacts are made between the end-effector and various environments. Therefore interaction forces must be controlled in tasks performed by robot manipulator. In general, there are two types of force control for robot manipulator. One is a stiffness control and the other is a hybrid position/force control. Stiffness control is that environment can be modeled as a spring and utilizes the desired normal force to determine the desired normal position. Hybrid position/force control, however, can be used for robot manipulator to track position and force trajectories simultaneously. This paper will compare the result of the hybrid position/force control method with that of the stiffness control method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.253-256
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• 1997

This paper proposes a control strategy of position and force control in the same direction based on hybrid position/force control. In order to control position and force in the same direction, a weighting matrix is introduced instead of a selection matrix suggested by Raibert and Craig. The major part of the controller output comes from the position controller when a position control error is large, from the force controller when a position control error is large. The proposed algorithm is implemented by the simulation and experiment focusing on the peg-in-hole task where friction exist significantly and is not constant. It also adopts and event control scheme for more efficient performance.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.638-641
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• 1992

In this paper, a hybrid position/force control scheme is proposed. The control scheme modifies the position command for force control against constraint surface of environment and is very simply designed and implemented. The merits of the control scheme are that it can cope with change of constraint conditions and small position inaccuracy of the environment. A constraint surface position observer is also proposed to reduce disturbances on controlled force.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.252-258
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• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.772-776
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• 1997

For a robot to perfom more versatile tasks, it is invitable for the robot's end-effector to come into contact with its environment. In thos case, to achieve better performance, it is necessary to properly control the contact force between the robot and the environment. In thos work, hybrid control theory is studied and is verified through experiment using a 3 DOF robot. In the experiment, two position/force controllers are used. Fist, proportional-integral-derivative controller is used as the controller for both position and force. Second, computed-torque method is used as the position controller, and proportional-integral-derivative controller is used as the force controller. For a proper modeling used in computed-torque method, the friction torque is measured by experiment, and compensation method is studied. The hybrid control method used in this experiment effectively control the contact force between the end-effector and the environment for various types of jobs.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1786-1790
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• 2004

The main objective of this paper is to analyze the performance of various force control algorithms in improving and adjusting the compliance of industrial robots in contact with their environment. Some of fundamental force control algorithms such as sensorless control, impedance control and hybrid position/force control are theoretically analyzed and simulated for various situations of an environment, and then a series of experiments using them were performed. In this paper, a control scheme to use position control in implementing the impedance control was investigated in order to nullify the effect of joint friction. The new reference trajectory is generated using contact force feedback and original desired trajectory. And an inner position control loop is designed to provide accurate position tracking for the new reference trajectory and good disturbance rejection. Experiments to insert a peg in a hole (so-called the peg-in-a-hole task) were performed with HILS (hardware-in-theloop simulation) system based on the results of the analyses and simulations on the characteristics of each control algorithm. The experiments showed that various force control methods improved the performance of robots in close contact with the environment by adjusting their compliance with respect to an arbitrary set of coordinates.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.743-746
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• 1996

A hybrid control scheme to regulate the force and position by dual arms is proposed, where two arms are treated as one arm in a kinematic viewpoint. Our approach is different from other hybrid control approaches which consider robot dynamics, in the sense that we employ a purely kinematic based approach for hybrid control, with regard to the nature of position-controlled industrial robots. The proposed scheme is applied to sawing task. In the sawing task, the trajectory of the saw grasped by dual arms is planned in an offline fashion. When the trajectory of the saw is planned to follow a line in a horizontal plane, 3 position parameters are to be controlled(i.e, two translational positions and one rotational position). And a certain level of contact force has to be controlled along the vertical direction(i.e., minus z-direction) not to loose the contact with the object to be sawn. Typical feature of sawing task is that the contact position where the force control is to be performed is continuously changing. Therefore, the kinematic mapping between the force controlled position and the joint actuators has to be updated continuously. The effectiveness of the proposed control scheme is experimentally demonstrated. The proposed hybrid control scheme can be applied to arbitrary dual arm systems, regardless of their kinematic structure and the number of actuated joints.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.24.2-27
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• 1996

This paper is a study on the fuzzy force control of a miniature gripper driven by piezoelectric bimorph actuator. The system is composed of two flexible cantilevers, a stepping motor, a laser displacement transducer and two semiconductor force sensors attached to the beams. Obtained results show that the present artificial finger system works well as a miniature gripper, which produces approximately 0.06N force in the maximum. Further, the fuzzy position/force control algorithm is applied to the soft-handing gripper for stable grasping of a object. It revealed that the fuzzy rule-based controller be efficient controller for the stable drive of the flexible miniature gripper. It also showed that two semiconductor strain gauges located in the flexible beam play an important roles for force control, position control and vibration suppression control.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.653-660
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• 2000

The automatization by industrial robot of today is merely rely on to the simple position repeating works, but requirements of research and development to the force control which would adapt positively to various restriction or contacting works to environment. In this paper, a learning control algorithm using, neural networks is proposed for the position and force control by a direct-drive robot. The proposed controller is the feedback controller to which the learning function of neural network is added on to and has a character of improving controller's efficiency by learning. The effectiveness of the proposed algorithm is demonstrated by the experiment on the hybrid position and force control of a parallelogram link robot with a force sensor.