• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.113-118
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• 1999

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important n the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.79-84
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.26-37
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller. feedback controller. and PID type time-varying auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.69.2-69
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.49-56
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• 2008

This paper proposes a PC-based open architecture controller for a multi-axis robotic manipulator. The designed controller can be applied for various multi-axes robotic manipulators since the motion controller is implemented on a PC with its peripheral devices. The accuracy of the controller based on the computed torque method has been measured with the dynamic model of manipulator. Since the controller is implemented in the PC-based architecture, it is free from the user circumstances and the operating environment. Dynamics of the manipulator have been compensated by the feed forward path in the inner loop and the resulting linear outer loop has been controlled by PD algorithm. Using the specialized language, it can be more efficient in programming and in driving of the multi-axis robot. Unlike the conventional controller that is used to control only a specific robot, this controller can be easily changed for various types of robots. This paper proposes a PC-based controller that has a simple architecture with its simple interface circuits than general commercial controllers. The maintenance and the performance of the controller can be easily improved for a specific robot. In fact, using a Samsung multi-axis robot, AT1, the controller performance and convenience of the PC-based controller have been verified by comparing to the commercial one.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.478-482
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C50) for robotic manipulators to achieve trajectorytracking angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide motion for robotic manipulators. In the proposed scheme, adapation laws are derived from the improved second stability analysis based on the indirect adaptive control theory.l The proposed control scheme is simple in structure, fast in computation, an suitable for implementation of real-time control. Moreover, this scheme does not requre an accurate dynamic modeling, nor values of manipulator paramenters and payload Performance of the adaptive controller is illustrated by exeperimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.645-652
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• 2010

For free motions, vibration suppression of single flexible manipulators has been one of the hottest research topics. However, for cooperative motions of multiple flexible manipulators, a little effort has been devoted for the vibration suppression control. So, the aim of this paper is to develop a hybrid force/position control and vibration suppression control scheme for multiple cooperation flexible manipulators handling a rigid object. In order to clarify the discussion, the motions of dual-arm experimental flexible manipulator are considered. Using the developed model, we control a robotic system with hybrid position/force control scheme. Finally, Experiments are performed, and a comparison of experimental results is given to clarify the validity of our control scheme.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.45-52
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• 2011

In the real-field of control cases for robot manipulators, there always exists a modeling error, which results the model has the uncertainties in its parameters and/or structure. In many modem applications, digital computers are extensively used to implement control algorithms to control such systems. The discretization of the nonlinear dynamic equations of such systems results in a complicated discrete dynamic equations. Therefore, it will be difficult to design a discrete-time controller to give good tracking performances in the presence of certain uncertainties. In this paper, a discrete-time sliding mode control algorithm for nonlinear and time varying robot manipulators with uncertainties is presented. Sufficient conditions for guaranteeing the convergence of the discrete-time SMC system are derived. As example simulations, the proposed SMC algorithm is applied to a two-link robotic manipulator with unknown dynamics. The results of the simulation indicate that the developed control scheme is effective in manipulators and electro-mechanical system control.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.618-623
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• 1992

In this paper robotic manipulators in which the joints exhibit a certain amount of elasticity are considered. Based on a feedback linearized model, sliding mode control system is designed. In the control system design, weak joint stiffness assumption does not needed. Simulation results are presented to verify the validity of the control scheme. A robustness analysis for a feedback linearized model is also given with respect to uncertainties on the robot parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2004-2009
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• 2003

A robust optimal control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method finding the Q weighting matrix is shown. Computer simulations have been done for a weight-lifting operation of a two-link manipulator and the result of the simulation shows that the proposed algorithm is very effective for a robust control of robotic systems.