• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.61.6-61
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• 2001

In this paper, we propose a method to analyze measured data from 3D Laser tracking system and to enhance precision performance of a Cartesian robot. Position data are obtained over the stroke of a Cartesian robot with variable speeds. The measured data is need to model errors with several different sources. In general, the error is a function of part accuracy, assembly accuracy, temperature, and control etc. After the sources of errors are identified, they are used to enhance precision performance. The proposed method is more complete than others because we use very accurate 3D Laser tracking system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.5-49
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• 2001

The Proportional-Integral-Derivative control scheme is widely used in industries. This paper investigates an alternative control paradigm for controlling lightweight Cartesian robot arms. Fuzzy PI control is used and validated experimentally by comparing performance with a conventional PID control algorithm. The results show the effectiveness of the fuzzy PI control. The fuzzy control shows superior performance in transient response over the conventional one.

• Journal of Drive and Control
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• v.14 no.3
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• pp.25-31
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• 2017

This study presents a methodology for simulating a unified approach that controls interaction force between tool and objective by using a synthesis method of robot interacting control law for stabilizing the transient process of motion. Root locus is used to analyze stabilization of motion deviation characteristics. Based on responses of motion deviation, contact force is derived to satisfy exponential stability and we generate control input with respect to motion trajectories and interaction force. Moreover, simulation is applied to experimental application of a Cartesian robot driven by two stepper motors, and the noise of feedback signals is considered as presence of system inaccuracies, and the unified approach of interaction force control is examined precisely.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1820-1823
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• 1997

For the Cartesian space position controlled robot, it is required to have the accurate mapping from the Cartesian space to the joint space in order to command the desired joint trajectories correctly. since the actual mapping from Cartesian space to joint space is obtained at the joint coordinate not at the actuator coordinate, uncertainty in Jacobian can be present. In this paper, two feasible neural network schemes are proposed to compensate for the kinematic Jacobian uncertainties. Uncertainties in Jacobian can be compensated by identifying either actuator Jacobian off-line or the inverse of that in on-line fashion. the case study of the stenciling robot is examined.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.518-521
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• 1995

In this paper, a learning control problem is formulated for cooperating multiple-robot manipulators with uncertain system parameters. The commonly held object is also assumed to be unknown and the multiple-robots themselfs experience uncertain operating conditions such as link parameters, viscous friction parameters, suctions, actuator bias, and etc. Under these conditions, the learning controllers designed for learning of uncertain parameters and robot control inputs for multiple-robot systems are shown to drive the multiple-robot manipulators to follow the desired Cartesian trajectory with the desired internal forces to the unknown object.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.243-245
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• 2007

This paper presents the implementation of teleoperation control of an omni-direction mobile robot. The master joystick robot has two degrees of freedom to control the movement of the slave mobile robot in the Cartesian space. In addition, the whole teleoperated control system is closed by the force feedback. The operator can feel the contact force as the slave robot makes contact with the environment. Experimental results show that the teleooerated control with force feedback has been successfully implemented.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.528-530
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• 1996

Because of the convenience of variable speed control and proportion of input current and torque, DC servo motor has been used as an actuator. With increasing development speed of robot and factory automation machinery, the actuator of excellent control characteristics is demanded. In this paper, The control characteristics of DC servo motor is tested by Fuzzy control with microprocessor and DC servo motor controller is designed for drive of the cartesian coordinate type robot. The control characteristics experimentation is realized to one axis position, two axes coordinate and circular motion control by experimental equipments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.176.1-176
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• 2001

Conventional researches almost have been focused on the one dimensional inverted pendulum. Recently, Sprenger et al[2] have researched a two dimensional inverted pendulum Observing human's action to control an inverted pendulum, one can recognize that human uses a three dimensional metier including the up and down motion. In this paper, we propose a fuzzy logic controller(FLC) of a new three dimensional inverted pendulum system. We derive a dynamic equation of the mechanism including a 3-axis cartesian robot and a inverted pendulum. We propose a design method of a fuzzy controller of the yaw and pitch angles of a inverted pendulum. In the design, the redundant degree-of-freedom(DOF) of the robot ...

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.57-64
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• 2024

In the industrial field, robots are used to increase productivity by replacing labors with dangerous, difficult, and hard tasks. However, failures of individual industrial robots in the entire production process may cause product defects or malfunctions, and may cause dangerous disasters in the case of manufacturing parts used in automobiles and aircrafts. Although requirements for early diagnosis of industrial robot failures are steadily increasing, there are many limitations in early detection. This paper introduces methods for diagnosing robot failures using sound-based data and deep learning. This paper also analyzes, compares, and evaluates the performance of failure diagnosis using various deep learning technologies. Furthermore, in order to improve the performance of the fault diagnosis system using deep learning technology, we propose a method to increase the accuracy of fault diagnosis based on an inference window. When adopting the inference window of deep learning, the accuracy of the failure diagnosis was increased up to 94%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.223-224
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• 2010