• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1111-1118
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• 2006

This paper covers topics related to the investigations for the problem of sensorless vibratory orienting of polygonal parts with high probability through dynamic simulation. The author's program for mechanical systems with changing topologies was experimentally validated and was used as a simulation and design tool for motion behaviors of the vibratory parts-orienting system in the dynamic environment. A flat level vibrating bar is proposed as a means of orienting parts. Dynamic manipulation, in which a part is repeatedly caught and tossed by the bar without sensing, forms the fundamental manipulation strategy. This paper presents how to plan vibratory manipulation strategies that can orient a small rigid polygonal part using interaction between the part and the vibrating bar without requiring sensing. The planned motion strategies have been experimentally validated to show how the dynamic simulation can be used to find favorable vibration parameters for a given part without knowledge of their initial orientations.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.304-312
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• 2011

In an oligopolistic market, only a few firms account for most or all of total production, e.g., automobile, steel, and computer industries. For a dynamic oligopolistic market with two firms competing in quantities, we show that supervisory control theory of discrete event systems provides a novel approach to solve the dynamic oligopoly problem with the aim of maximizing the profits of both firms. Specifically, we show that the controllability, observability, and nonblocking property (which are the core concepts in supervisory control theory) are the necessary and sufficient conditions for two oligopolistic firms in disequilibrium to eventually reach equilibrium states of maximizing the profits of both firms.

• Asia pacific journal of information systems
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• v.15 no.1
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• pp.25-44
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• 2005

This study examines control types of IS outsourcing project management focusing on two sets of questions: What control types are implemented during IS outsourcing projects? How various control types affect the performance of IS outsourcing projects. In order to meet these objectives, four control types are developed using typology-approach: dynamic, contract-oriented, partnership-oriented, and passive. And then four control types are identified based on taxonomy-approach using cluster analysis from 66 projects: dynamic, contract-oriented, passive, and middle. The result shows that the derived taxonomy-types are similar to the typology-types except partnership-oriented type. The result also indicates that dynamic and contract-oriented types are in the highest performance, while passive type is in the least performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.583-586
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• 2003

There are electric four-wheeled vehicles to assist elder people. Because of the vehicles'dynamic characteristic such as impossible to move abeam, it is difficult for these people who has little experience and has little knowledge to drive. Also to judge the future state of dynamic obstacles and to decide how to elude them safely are more difficult. We installed the predictive fuzzy controller(evaluates the future states which several kinds of operation candidates were done and chooses the best one) that modeled humans'algorithms in the system. Human predicts the future states of dynamic obstacles and chooses an operation(wait, steer, go back, etc) to elude safely. To elude dynamic obstacles flexibly, we added expert's knowledge for safe driving to this controller. In this paper, we propose the intelligent soft driving system by the controller that can elude dynamic obstacles safely, and we confirm the effectiveness by a simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.302-305
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• 2003

In this paper, dynamic behaviors of a small-sized flying robot with 4 rotors propelled by DC motor are discussed, and a control scheme based on the dynamic model to make stable flying motions, i.e., hovering, take-off, cruising behavior, etc. is proposed. The experimental results via some flying tests show good performances for practical use. The flying robot with 6DOF is controlled only 4 DOF, and the rest of two DOF are remained under the dynamic constraints. How to give the stability of all positions and orientations and to make the omni-directional motions in spite of such restrictions is analyzed. The proposed control scheme composes of two stages. First, PD control inputs for the trust-force and orientation are calculated, next the control inputs are distributed to each rotor by using a sort of Jacobian matrix. To design and control of a low cost - small sized flying robot, vibrated gyro sensor, cheap accelerometer, IR, and ultra sonic sensors are selected.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.150-153
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• 2007

The intent of this paper is to describe a neural network structure called multi dynamic neural network(MDNN), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the MDNN, are described. Computer simulations are demonstrate the effectiveness of the proposed learning using the MDNN.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.7
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• pp.406-412
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• 2013

A hybrid heat pump is under development with the goal of utilizing 120% of primary energy resources. A plate heat exchanger is added between the compressor and air-cooled condenser of an ordinary heat pump to heat water. For successful operation of the heat pump, it is necessary to develop a control algorithm under various operating conditions. As a virtual test bed for that purpose, a dynamic model has been developed, to simulate its dynamic behavior. It was modeled in transient one-dimensions, with varying phase lengths considered. The model was implemented in Matlab and Simulink. Simulation results were effectively applied to design a control algorithm. They also provided physical insight into how to design and operate the system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2024-2029
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• 2005

In this paper, it is shown how a mobile robot can navigate with high speed in dynamic real environment. In order to achieve high speed and safe navigation, a robot collects environmental information. A robot empirically memorizes locations of high risk due to the abrupt appearance of dynamic obstacles. After collecting sufficient data, a robot navigates in high speed in safe regions. This fact implies that the robot accumulates location dependent environmental information and the robot exploits its experiences in order to improve its navigation performance. This paper proposes a computational scheme how a robot can distinguish regions of high risk. Then, we focus on velocity control in order to achieve high speed navigation. The proposed scheme is experimentally tested in real office building. The experimental results clearly show that the proposed scheme is useful for improving a performance of autonomous navigation. Although the scope of this paper is limited to the velocity control in order to deal with unexpected obstacles, this paper points out a new direction towards the intelligent behavior control of autonomous robots based on the robot's experience.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.141-147
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• 2008

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.

• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.191-196
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• 2008

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are provided to demonstrate the effectiveness of the proposed learning using the DNP.