• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.295-304
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• 2000

In the teleoperation system, force and velocity signals are communicated between a master and a slave robot. The addition of force feedback to a teleoperation system benefits the operator by providing more information to perform given tasks especially for tasks requiring contact with environment. When the master and slave arms are located in different places, time delay is unavoidable and it is well known that the system can become unstable when even a small time delay exists in the communication channel. The control scheme proposed in this paper is based on the estimator with virtual master model. Delayed signal from the master robot can be replaced by the estimated signal with the virtual master model. This control scheme makes the teleoperation system stable for the given time delay while the conventional scheme is not. This new control scheme is verified through numerical simulations and an experiments using the dual axis testbed of the teleoperation system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.41-47
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• 2000

A better tracking performance can be achieved, if visual sensors such as CCD cameras are used in controling a robot manipulator, than when only relative sensors such as encoders are used. However, for precise visual servoing of a robot manipulator, an expensive vision system which has fast sampling rate must be used. Moreover, even if a fast vision system is implemented for visual servoing, one cannot get a reliable performance without use of robust and stable inner joint servo-loop. In this paper, we propose a dynamic control scheme for robot manipulators with eye-in-hand camera configuration, where a dynamic learning controller is designed to improve the tracking performance of robotic system. The proposed control scheme is implemented for tasks of tracking moving objects and shown to be robust to parameter uncertainty, disturbances, low sampling rate, etc.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.100-107
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• 1998

This paper presents the development of estimation model and control method based on the new robot vision. This proposed control method is accomplished using the sequential estimation scheme that permits placement of the rigid body in each of the two-dimensional image planes of monitoring cameras. Estimation model with six parameters is developed based on the model that generalizes known 4-axis scara robot kinematics to accommodate unknown relative camera position and orientation, etc. Based on the estimated parameters, depending on each camera the joint angle of robot is estimated by the iteration method. The method is experimentally tested in two ways, the estimation model test and a three-dimensional rigid body placement task. Three results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as assembly and welding.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.3
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• pp.245-256
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• 2017

In this study, we describe a new approach to real-time implementation of working path control for the forging and casting manufacturing process by vertical type articulated robot system. The proposed control scheme is simple in structure, fast in computation, and useful for real-time control of factory automation based on robot system. Moreover, this scheme does not require any accurate parameter information, nor values of the uncertain parameters and payload variations. Reliability of the proposed controller is proved by simulation and experimental results for robot manipulator consisting of arm with six degrees of freedom under the variation of payloads and tracking trajectories in Cartesian space and joint space. The vertical type articulated robot manipulator with six axes made in SMEC Co., Ltd. has been used for real-time implementation test to illustrate the enhanced working path control performance for unmanned automation of the forging and casting manufacturing process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.11
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• pp.753-763
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• 2015

This paper proposes a decentralized robust adaptive neural network control scheme using multiple radial basis function neural networks for electrically driven robot manipulators with bounded input voltages in the presence of uncertainties. The proposed controller considers both robot link dynamics and actuator dynamics. Practically, the controller gain coefficients applied at each joint may be nonlinear time-varying and the input voltage at each joint is saturated. The proposed robot controller overcomes the various uncertainties and the input voltage saturation problem. The proposed controller does not require any robot and actuator parameters. The adaptation laws of the proposed controller are derived by using the Lyapunov stability analysis and the stability of the closed-loop control system is guaranteed. The validity and robustness of the proposed control scheme are verified through simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.355-355
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• 2000

The position control accuracy of a robot manipulator is significantly deteriorated when a long arm robot is operated at a high speed. This paper presents a very simple sliding mode control which eliminates multiple mode residual vibration in a 개bot manipulator. The neural network is used to avoid that sliding mode condition is deviated due to the change of system parameter and disturbance. This paper is suggested control system which designed by sliding mode controller using neural network. The effectiveness of proposed scheme is demonstrated through computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.883-890
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• 2010

This paper proposes tip position control system which uses a visual marker to determine the tip position of a robot manipulator. The main idea of this paper is to introduce visual marker for the tracking control of a robot manipulator. Existing researches utilize stationary markers to get pattern information from them. Unlike existing researches, we introduce visual markers to get the coordinates of them in addition to their pattern information. Markers need not be stationary and the extracted coordinate of markers are used as a reference trajectory for the tracking control of a robot manipulator. To build the proposed control scheme, we first obtain intrinsic parameters through camera calibration and evaluate their validity. Secondly, we present a procedure to obtain the relative coordinate of a visual marker with respect to a camera. Thirdly, we derive the equation for the kinematics of the SCORBOTER 4pc manipulator which we use for control of manipulator. Also, we provide a flow diagram of entire visual marker tracking system. The feasibility of the proposed scheme will be demonstrated through real experiments.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.409-411
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• 1991

This paper presents a collision avoidance scheme for redundant robot manipulators based on the Configuration Control Scheme. We set a center line through the free space. And we use the redundancy to put the robot links, around the center line as close as possible to avoid the collision with obstacles. Computer simulation shows the effectiveness of this approach.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.15-18
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• 2003

This paper presents an adaptive control scheme for parking or regulating a nonholonomic mobile robot of an unicycle type with parameter uncertainty. The kinematics can be described with Brockett's nonholonomic integrator. The control law is designed in cylindrical coordinates together with the estimation law for the uncertain parameters such that the controlled signals converge to zero while guaranteeing the boundedness of the estimation errors. The effectiveness of the proposed scheme is demonstrated using simulations.