• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.573-578
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• 2011

We propose a switching-based adaptive state feedback controller for a class of nonlinear systems that have uncertain nonlinearity. The base of the proposed conditions on the nonlinearity is the feedforward form, then it is extended via a nonlinear function containing all the states and the control input. As a result, more generalized systems containing feedforward and nonfeedforward terms are allowed as long as the ratio condition of the nonlinear function is satisfied. Moreover, the information on the growth rate of nonlinearity is not required a priori in our control scheme.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.875-879
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• 1998

A fault on the transmission line results in the variation of reactance and parametric uncertainties in the power system dynamics. In this case, we need a robust control to cope with these uncertainties. A sliding mode control, a sort of robust control, is known to be robust to parametric or state-dependent uncertainties if the bounding function of uncertain terms is determined a priori. However, in general, we can not readily determine the bounding function for the complex systems. Hence, in this paper we introduce a fuzzy system which can estimate the bounding function in relatively simple way. By the use of the proposed fuzzy system, determination of bounding function is made easier. We applied the proposed scheme to the stabilization of power system under the sudden fault on the transmission lines. The simulation result verifies the effectiveness of the scheme.

• Structural Engineering and Mechanics
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• v.39 no.5
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• pp.733-750
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• 2011

Recently, identification of modal parameters using the response only data has attracted considerable attention particularly where the classic modal testing methods is difficult to conduct. One drawback of the response only data, also known as Operational Modal Analysis (OMA), is that only the unscaled mode shapes can be obtained which restricts the applications of OMA. The Mass change method is a usual way to scale the operational mode shapes. In this article a new method is proposed to optimize the additive mass for scaling of the unscaled mode shapes from OMA for which a priori knowledge of the Finite Element model of structure is required. It is shown that the total error of the scaled mode shapes is minimized using the proposed method. The method is validated using a numerical case study of a beam. Moreover, the experimental results of a clamped-clamped beam demonstrate the applicability of the method.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1228-1230
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• 1996

A neural network(NN) mechanism is proposed to modify the gait of a biped robot that walks on sloping surface using sensory inputs. The robot starts walking on a surface with no priori knowledge of the inclination of the surface. By accumulating experience during walking, the robot improves its walking gait and finally forms a gait that is adapted to the surface inclination. A neural controller is proposed to control the gait which has 72 reciprocally inhibited and excited neurons. PI control is used for position control, and the neurons are trained by a reinforcement learning mechanism. Experiments of static gait learning and pseudo dynamic learning are performed to show the validity of the proposed reinforcement learning mechanism.

• Journal of Korean Society for Quality Management
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• v.25 no.2
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• pp.169-188
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• 1997

The purpose of this study is concerned with suggesting a new a, pp.oach to evaluating the overall product quality in the sense of the relative efficiency of products, whose quality is measured with 8-dimensional attributes, suggested by Garvin. The attributes included 8 quality measures, that is, performance, features, reliability, conformance, durability, serviceabilit, aesthetics, and perceived quality. This study, also, introduced DEA(Data Envelopment Analysis) as an evaluation tool to tackle the problem of how to measure one product against another when each product can be measured along a number of dimensions, and given that there exists no a priori satisfactory weighting scheme to combine these dimensions into an overall rating for each products. In order to a, pp.y the DEA to evaluating the products, we must define two concepts, such as DMU(Decision Making Units) and input-output relationship. Finally, the suggested method in this study was validated through a case study of the electric jar, and this DEA a, pp.oach can be used in evaluating the other products with multi-attrribute quality.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.130-135
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• 2004

This paper presents a 3-D localization of an autonomous underwater vehicle(AUV). Conventional methods of localization, such as LBL or SBL, require additional beacon systems, which reduces the flexibility and availability of the AUV We use a digital compass, a pressure sensor, a clinometer and ultrasonic sensors for localization. From the orientation and velocity information, a priori position of the AUV is estimated based on the dead reckoning. With the aid of extended Kalman filter algorithm, a posteriori position of the AUV is estimated by using the distance between the AUV and a mother ship on the surface of the water together with the water depth information from the pressure sensor. Simulation results show the possibility of practical application of the method to autonomous navigation of the AUV.

• Publications of The Korean Astronomical Society
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• v.37 no.1
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• pp.1-11
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• 2022

During the course of analysing both single-dish and very long baseline interferometry (VLBI) data obtained from the Korean VLBI Network (KVN), we found a systematic offset between flux density measurements from different antennas. We were able to attribute a majority of the systematic offsets to changes in the "a priori" antenna gains, which were found to have varied up to 10 percent at 22 GHz and up to 30 percent at 43 GHz. Using historical calibrator observations, we present a revised set of gains that may be applied to KVN data taken from 2015 August to 2019 January. Application of the revised gains to the KVN results in a consistency of correlated flux density measurements between the three baselines of approximately five percent. We found that images from the recalibrated data typically have a 50 percent higher dynamic range, with some cases showing an increase of dynamic range of up to a factor of three.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.12
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• pp.1306-1316
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• 1990

A controller using a multilayer neural network is proposed to the dynamic control of a PUMA 560 robot arm. This controller is developed based on an error back-propagation (BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it is used as a commanded feedforward torque generator. A Proportional Derivative (PD) feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the manipulator as well as the PD feedback error torque. No a priori knowledge on system dynamics is needed and this information is rather implicitly stored in the interconnection weights of the neural network. In another experiment, the neural network was trained with the current, past and future positions only without any use of velocity sensors. Form this thim window of position values, BP network implicitly filters out the velocity and acceleration components for each joint. Computer simulation demonstrates such powerful characteristics of the neurocontroller as adaptation to changing environments, robustness to sensor noise, and continuous performance improvement with self-learning.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.16-19
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• 2003

This paper describes research on mental commit robot that seeks a different direction from industrial robot, and that is not so rigidly dependent on objective measures such as accuracy and speed. The main goal of this research is to explore a new area in robotics, with an emphasis on human-robot interaction. In the previous research, we categories robots into four categories in terms of appearance. Then, we introduced a cat robot and a seal robot, and evaluated them by interviewing many people. The results showed that physical interaction improved subjective evaluation. Moreover, a priori knowledge of a subject has much influence into subjective interpretation and evaluation of mental commit robot. In this paper, 133 subjects evaluated the seal robot, Paro by questionnaires in an exhibition at the National Museum of Science and Technology in Stockholm, Sweden. This paper reports the results of statistical analysis of evaluation data.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.831-844
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• 2008

Since cooperatives consist of many distinct members in the management environment and characteristics, it is necessary to make similar cooperatives into a few groups for the effective risk management of cooperatives' mutuality bank. This paper is a priori research for suggesting a guidance for effective risk management of cooperatives with different management strategy. For such purpose, we propose a way to group the members of cooperative's mutuality bank. The 30 continuous variables which is relative to cooperatives' management status are considered and six factors are extracted from those variables through factor analysis with empirical consideration to avoid wrong grouping and to enhance the practical interpretation. Based on extracted six factors and additional 3 categorical variables, six representative groups are derived by the two step clustering analysis. These findings are useful to execute a discriminatory risk management and other management strategy for a mutuality bank and others.