• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.193-204
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• 2016

This paper presents an anthropomorphic finger prosthesis for amputees whose proximal phalanx is mutilated. The finger prosthesis to be proposed is able to make the amputees to perform the natural motion such as flexion/extension as well as self-adaptive grasping motion as if normal human finger does. The mechanism of finger prosthesis with three degrees-of-freedom (DOFs) consists of two five-bar and one four-bar linkages. Two passive components composed of torsional spring and mechanical stopper and only one active joint are employed in order to realize an underactuation. Each passive component is installed into the five-bar linkage. In order to activate the finger prosthesis, it is required for the user to flex and extend the remaining proximal phalanx on the metacarpophalangeal (MCP) joint, not an electric motor. Thus the finger prosthesis conducts not only the natural motion according to his/her intention but also the grasping motion through the deformation of springs by the object for human finger-like behavior. In order to reveal the operation principle of the proposed mechanism, kinematic analysis is performed for the linkage design. Finally both simulations and experiments are conducted in order to reveal the design feasibility of the proposed finger mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.145-149
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• 1993

This paper considers the adaptive predictive control problem of a system characterized by a multiplexed measurements and multirate sampling mechanism. Plant outputs are measured in various sampling rates through a multiplexed measurement system where a single common instrument is shared by several controllers. In general, output measurement sampling rate is assumed to be slower that input update rate. An adaptive predictive control algorithm is developed for systems with multiplexed measurements.

• Proceedings of the KIEE Conference
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• 1983.07a
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• pp.135-138
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• 1983

This paper studies a variable structure adaptive model following control system which can control a plant in which the parameters of the controlled plant can not be estimated because they vary with time and in which the controlled plant has noise. The values of the feedback gain matrices for given states are obtained the equivalent control law, and the adaptive controller has been designed using the adaptive mechanism which switches the matrices. The adaptive controller minimizes the state error vector, that is, the difference between the state vector of the model and the state vector of the controlled plant. A controlled plant which has time varying parameters, a controlled plant which has only noise, and a controlled plant which has both have been controlled by the designed adaptive controller. The continuous single input-output system has been analysed by computer. This control system may be used to control practical systems by the addition of a microcomputer.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.03a
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• pp.211-223
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• 1995

The purpose of the present study is to examine shearing mechanism through rigidplastic finite element analysis. Difficulties arise in simulating shearing process due tothe narrow shear band formation andlackof proper fracture resolve these difficulties by using adaptive mesh generation crriterion. The simulation results are obtained for various punch clearances and these are compared with existing experimental results. It is shown that FEM simulation technique can be used to further understand the shearing mechanism.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.9-18
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• 2022

As the COVID-19 continues, the demand for robotic technology that can be applied in face-to-face tasks such as delivery and transportation, is increasing. Although these technologies have been developed and applied in various industries, the robots can only be operated in a tidy indoor environment and have limitations in terms of payload. To overcome these problems, we developed a 2 degree of freedom(DOF) environmental adaptive robot leg with a double 1-DOF counterbalance mechanism (CBM) based on wire roller. The double 1-DOF CBM is applied to the two revolute joints of the proposed robot leg to compensate for the weight of the mobile robot platform and part of the payload. In addition, the link of the robot leg is designed in a parallelogram structure based on a belt pulley to enable efficient control of the mobile platform. In this study, we propose the principle and structure of the CBM that is suitable for the robot leg, and design of the counterbalance robot leg module for the environment-adaptive control. Further, we verify the performance of the proposed counterbalance robot leg by using dynamic simulations and experiments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.143-156
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• 2024

Federated Learning (FL) has emerged as a potent methodology for decentralized model training across multiple collaborators, eliminating the need for data sharing. Although FL is lauded for its capacity to preserve data privacy, it is not impervious to various types of privacy attacks. Differential Privacy (DP), recognized as the golden standard in privacy-preservation techniques, is widely employed to counteract these vulnerabilities. This paper makes a specific contribution by applying an existing, task-specific adaptive DP mechanism to the FL environment. Our comprehensive analysis evaluates the impact of this mechanism on the performance of a shared global model, with particular attention to varying data distribution and partitioning schemes. This study deepens the understanding of the complex interplay between privacy and utility in FL, providing a validated methodology for securing data without compromising performance.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.3
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• pp.173-181
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• 2012

The size and layout of user interface components need to be optimally designed in terms of reachability, visibility, clearance, and compatibility in order for efficient and effective use of products. The present study develops an ergonomic design method which optimizes the size and layout of user interface components using adaptive genetic algorithm. The developed design method determines a near-optimal design which maximizes the aggregated score of 4 ergonomic design criteria (reachability, visibility, clearance, and compatibility). The adaptive genetic algorithm used in the present study finds a near-optimum by automatically adjusting the key parameter (probability of mutation) of traditional genetic algorithm according to the characteristic of current solutions. Since the adaptive mechanism partially helps to overcome the local optimality problem, the probability of finding the near-optimum has been substantially improved. To evaluate the effectiveness of the developed design method, the present study applied it to the user interface design for a portable wireless communication radio.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.157-160
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• 2001

This paper has been studied a Adaptive Mutation rate Genetic Algorithm Processor. Genetic Algorithm(GA) has some control parameters such as the probability of bit mutation or the probability of crossover. These value give a priori by the designer There exists a wide variety of values for for control parameters and it is difficult to find the best choice of these values in order to optimize the behavior of a particular GA. We proposed a Adaptive mutation rate GA within a steady-state genetic algorithm in order to provide a self-adapting mutation mechanism. In this paper, the proposed a adaptive mutation rate GAP is implemented on the FPGA board with a APEX EP20K600EBC652-3 devices. The proposed a adaptive mutation rate GAP increased the speed of finding optimal solution by about 10%, and increased probability of finding the optimal solution more than the conventional GAP

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.9
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• pp.569-575
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.4
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• pp.259-266
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• 1987

In order to drive motor control system precisely, the motor is to be controlled by mmfs and current with sinusoidal waveforms. In this paper the Delta Modulation (DM) Technique is used for generating PWM pulse with sinusoidal waveform. However the motor currents yet contain odd harmonics due to leakage inductances, speed and exitation. To reduce harmonics, the parameter adaptive control method is introduced. That is, Req.C parameter of Delta Modulator is controlled adaptively by parameter adaptor. The adaptive signal is achieved by the difference between motor current and reference waveform, and this signal is converted to the voltage commend signal by adaptive mechanism. The test reslts show that this system is operated smoothly over a wide range of motor speed and motor current is controlled to be sinusoidal waveform adaptively.