• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.168-173
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• 1991

A neural optimization network is proposed to control the redundant robot manipulators in an environment with the obstacle. The weightings of the network are adjusted by considering both the joint dexterity and the capability of collision avoidance of joint differential motion. The fuzzy rules are proposed to determine the capability of collision avoidance of each joint. To show the validities of the proposed method, computer simulation results are illustrated for the redundant robot of the planner type with three degrees of freedom.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.11
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• pp.941-949
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• 1989

This two-part paper presents a control method that allows for stable interaction of a robot manipulator with environment. In part 1, we focus on the input output relationships (unstructured modeling) of the robot and environment dynamics. This analysis leads to a general condition for stability of the robot and environment taken as a whole. This stability condition, for stable maneuver, prescribes a finite sensitivity for robot and environment where sensitivity of the robot (or the environment) is defined as a mapping forces into displacement. According to this stability condition, smaller sensitivity either in robot or in environment leads to narrower stability range. In the limit, when both systems have zero sensitivity, stability cannot be guaranteed. These models do not have any particular structure, yet they can model a wide variety of industrial and research robot manipulators and environment dynamic behavior. Although this approach of modeling may not lead to and design procedure, it will allow us to understand the fundamental issues in stability when a robot interacts with an environment.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.220-227
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• 1999

The position control accuracy of a robot arm is significantly deteriorated when a long slender arm robot is operated at a high speed. In this case, the robot arm needs to be modeled as a flexible structure, not a rigid one, and its control system needs to be designed with its elastic modes taken into account. In this paper, the vibration control scheme of a one-link flexible manipulator using adaptive input shaper in conjunction with PID controller is presented. The robot consists of a flexible arm manufactured with a thin aluminium plate, an AC servo motor with a harmonic drive for speed reduction, an optical encoder and an accelerometer. On-line identification of the vibration mode is done using the pruned decimation-in-time FFT algorithm to estimate the parameter of the input shaper. Experimental results of the flexible manipulator with a PID controller and input shaper are provided to show the effectiveness of the advocated controllers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.754-758
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS320C50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator, In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters we determined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.298-308
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• 2000

In this paper a new two-arm cooperative assembly(or insertion) algorithm is proposed. As a force-guided control method for the cooperative assembly the adaptive accommodation controller is adopted since it does not require any complicated contact state analysis nor depends of the geometrical complexity of the assembly parts. Also the RMRC(resolved motion rate control) method using a relative jacobian is used to solve inverse kinematics for two manipulators. By using the relative jacobian the two cooperative redundant manipulators can be formed as a new single redundant manipulator. Two arms can perform a variety of insertion tasks by using a relative motion between their end effectors. A force/torque sensing model using an approximated penetration depth calculation a, is developed and used to compute a contact force/torque in the graphic assembly simulation . By using the adaptive accommodation controller and the force/torque sensing model both planar and a spatial cooperative assembly tasks have been successfully executed in the graphic simulation. Finally through a cooperative assembly task experiment using a humanoid robot CENTAUR which inserts a spatially bent pin into a hole its feasibility and applicability of the proposed algorithm verified.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1573-1576
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• 1997

In this paper we present an associative menory network(AMN) controller for learning of robot trajectories. We use AMN controller in order to improve the performance of conventional learning control, e.g. RCL, which had studied by Sadegh et al. Computer simulations show the feasibility and effectiveness of the proposed AMN controller.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.317-320
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• 1986

A co-operative position control is proposed for two robot manipulators with 5 degree of freedoms to transfer an object following a specified trajectory, where each manipulator is assumed to change the posture of its end effector without releasing the object.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1042-1046
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• 1993

This paper describes a control scheme for a robot manipulator system which uses visual information to position and orientate the end-effector. In this scheme, the position and orientation of the target workpiece with respect to the base frame of the robot are assumed to be unknown, but the desired relative position and orientation of the end-effector to the target workpiece are given in advance. The control scheme directly integrates visual data into the servoing process without subdividing the process into determination of the position and orientation of the workpiece and inverse kinematics calculation. A neural network system is used for determining the change in joint angles required in order to achieve the desired position and orientation. The proposed system can be control the robot so that it approach the desired position and orientation from arbitrary initial ones. Simulation for the robot manipulator with six degrees of freedom will be done. The validity and the effectiveness of the proposed control scheme will be verified by computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.428-433
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• 1994

This investigates the feasibility of applying fuzzy ogic controllers to the motion tracking control of a direct drive robot manipulator to deal with highly nonlinear and time-varying dynamics associated with robot motion. A fuzzy logic controller with narrow shape of membership functions near zero and wide shape far away zero is analyzed. Simulation and experimental studies have been conducted for a 2 degree of freedom direct drive SCARA robot to evaluate control performances, Fuzzy logic controllers have shown control performances that are often better, or at least, as good as those of conventional PID controllers. Furthermore, the control performance of fuzzy logic controllers can be improved by selecting membership functions of narrow shapes near zero and wide shapes far away zero.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.35-47
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• 2004

In this paper presents a new approach to the design and real-time implementation of fuzzy control system based-on digital signal processors(DSP:IMS320C80) in order to improve the precision and robustness for system of industrial robot(Dual-Arm with 8 joint Robot). The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The IMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller(SOFC) for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a FLC(Fuzzy Logic Controller), one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult SOFC is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed SOFC scheme is simple in structure, Int in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.