• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.507-512
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• 1997

This paper presents a method of finding optitnal joint torques of two robots when they hold an object simultaneously. Although the importance of the multiple cooperating robot system increases for more flcviblc ni;mufacturing automation, dynamic solutions to multi-robot system forming closcd kinematic chain is not easy to find. Newton-Eulcr approach is used for the dynamic formulation of two robots fonn~ng closcd kincmatic chains gmsping a rigid body object. The nrcthodology to optimize the joint torques to satisfy given criterta and obtain bettcr control of the system is discussed. The scheme is illustrated by an example.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.131-139
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• 1995

In this study, small size stacker Crane for automatic ware house and interface circuit is designed and manufactured. IBM-PC is used as a controller. At 50kg$_{f}$ load, optimal motion velocity is 20 mm/min for X and Y axis and 12 mm/min for Z axis. Position fesolution is 0.005 mm and repeatability is .+-. 0.025 mm. Through characteristic experiment, effectiveness of the designed and manufactured stacker crane. PC control program, and design of interface circuit and construction of control system are shown. From these results, the developed stacker crane can be apply to FMS(Flexible Manufacturing System) and FA(Factory Automation) of industrial field.d.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

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 bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic 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 SCAEA robot.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.348-352
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• 1992

At present, the manufacturing industry is in a process of great change of circumstances like meeting demands to involve a great variety of types and shorter product life and thus more flexible manufacturing. These changes cause the larger number of different tools and frequent tool changes, which lead to the considerable losses in productive time and the high amount of capital tied up in the tool area. In our country, for the most part, the individual tool are still being presetted according to a data sheet and the measured values are entered, output in a list manually or via punched tapes. This usually takes a considerable amount time and lead to a high error rate. This paper describes a computer controlled tool data management system combined with the bar code tool identification labeled on cutting tools.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.786-794
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• 1998

This paper proposes an automatic microshaping technology using laser and applies it to implementation of semicutting control system of the panel inside which a car air bag is equipped. Since it is impossible to project laser directly onto the desired working point of a target panel due to fixedness of laser generator, we reflect the generated laser, using reflection mirrors and focusing lenses, to project onto the desired working point. Also, in order to conduct an uniform semicutting control with constant width and depth, we control the end-effector of manipulator, which grasp the laser reflection mirror, to track working path with constant speed and orientation. The validity and effectiveness of the proposed methods are checked through experiments tracking a path formatted with straight lines and arcs.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.153-158
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• 2000

This paper addresses an intelligent robot control system using an off-line programming to teach a precise assembly task of electronic components in a flexible way. The investigated task consists of three job: heat caulking test, soldering on a circuit board, and checking of soldering defects on the back cover of a camera. This study investigates the remodelling of the most complicated cell in terms of the accuracy and fault rate among the twelve cells in a camera back-cover assembly line. We have attempted to enhance back-cover assembly line. We have attempted to enhance soldering quality, to add task flexibility, to reduce failure rate, and to increase product reliability. This study modifies the cell structure, and improves the soldering condition. The developed all system implements the real-time control of assembly with vision data, and realized an easier task teaching on off-line programming.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.4
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• pp.36-43
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• 1992

This paper presents a hierarchical real-time operation control and monitoring scheme of the FMS/CIM center which has been implemented at the Automation and Systems Research Institute of Seoul National University. The hierarchical structure of the whole scheme consists of three lavers. The upper layer is in charge of on-line scheduling, computer network control, shop-floor monitoring and command generation for AGV dispatching, machining, assembly, inspection, set-up, etc. The middle layer has six modules, which are installed in the FMS host computer with the upper layer and run on the multi-tasking basis. Each module is connected to one of six cell controllers distributed in the FMS model plant and transfers operation command down to each cell controller through the Ethernet/TCP-IP local area network. The lower layer is comprised of six cell control software modules for machining cell, assembly cell, inspection cell, set-up stations. AS/RS and AGV. Each cell controller reports the status of the manufacturing facilites to the middle layer as well as ecxecuting the appropriate sequence control of the manufacturing processes.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.495-505
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• 2008

This paper describes modeling Voltage Sourced Inverter (VSI) type Flexible AC Transmission System (FACTS) controllers and control methods for power system dynamic stability studies. The considered FACTS controllers are the Static Compensator (STATCOM), the Static Synchronous Series Compensator (SSSC), and the Unified Power Flow Controller (UPFC). In this paper, these FACTS controllers are derived in the current injection model, and it is applied to the linear and nonlinear analysis algorithm for power system dynamics studies. The parameters of the FACTS controllers are set to damp the inter-area oscillations, and the supplementary damping controllers and its control schemes are proposed to increase damping abilities of the FACTS controllers. For these works, the linear analysis for each FACTS controller with or without damping controller is executed, and the dynamic characteristics of each FACTS controller are analyzed. The results are verified by the nonlinear analysis using the time-domain simulation.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.253-262
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• 2008

This paper presents a framework for decentralized control of self-organizing swarm systems based on the artificial potential functions (APFs). The framework explores the benefits by associating agents based on position information to realize complex swarming behaviors. A key development is the introduction of a set of association rules by APFs that effectively deal with a host of swarming issues such as flexible and agile formation. In this scheme, multiple agents in a swarm self-organize to flock and achieve formation control through attractive and repulsive forces among themselves using APFs. In particular, this paper presents an association rule for swarming that requires less movement for each agent and compact formation among agents. Extensive simulations are presented to illustrate the viability of the proposed framework.