• Journal of Biomedical Engineering Research
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• v.26 no.5
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• pp.257-264
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• 2005

This paper proposes an ionic polymer metal composite (IPMC) based artificial muscle to be applicable to the Myoelectric hand prosthesis. The IPMC consists of a thin polymer membrane with metal electrodes plated chemically on both faces, and it is widely applying to the artificial muscle because it is driven by relatively low input voltage. The control commands for the IPMC-based artificial muscle is given by electromyographic (EMG) signals obtained from human forearm. By an intended contraction of the human flexor carpi ulnaris and extensor carpi ulnaris muscles, we investigated the actuation behavior of the IPMC-based artificial muscle. To obtain higher actuation force of the IPMC, the single layered as thick as $800[{\mu}m]$ or multi-layered IPMC of which each layer can be as thick as $178[{\mu}m]$ are prepared. As a result, the bending force was up to the maximum 12[gf] from 1[gf] by actuating the single layered IPMC with $178[{\mu}m]$, but the bending displacement was reduced to 6[mm] from 30[mm]. The experimental results using an implemented IPMC control system show a possibility and a usability of the bio-mimetic artificial muscle.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.465-470
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• 2012

This paper proposes a distributed autonomous control method of swarm robot behavior strategy based on artificial immune system and an optimization strategy for artificial immune system. The behavior strategies of swarm robot in the system are depend on the task distribution in environment and we have to consider the dynamics of the system environment. In this paper, the behavior strategies divided into dispersion and aggregation. For applying to artificial immune system, an individual of swarm is regarded as a B-cell, each task distribution in environment as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows: When the environmental condition changes, the agent selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other agent using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. In order to decide more accurately select the behavior strategy, the optimized parameter learning procedure that is represented by stimulus function of antigen to antibody in artificial immune system is required. In this paper, particle swarm optimization algorithm is applied to this learning procedure. The proposed method shows more adaptive and robustness results than the existing system at the viewpoint that the swarm robots learning and adaptation degree associated with the changing of tasks.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.8
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• pp.1105-1110
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• 2011

This paper presents an improved direct torque control based on artificial neural networks technique. The major problem that is usually associated with DTC drive is the high torque(speed) ripple. To overcome this problem a torque hysteresis band with variable amplitude is proposed based on artificial neural networks. The artificial neural networks proposed controller is shown to be able to reducing the torque(speed) ripple and dependency on motor parameter and to improve performance DTC especially at high speed and reversal running.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.34-41
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• 2011

This paper presents a frequency-response test performed on an antagonistic actuation system consisting of two Mckibben pneumatic artificial muscles and a pneumatic circuit. A linear model, capable of estimating the dynamic characteristics of the antagonistic system in the operating range of pneumatic artificial muscles, was optimally calculated based on frequency-response results and applied to a multiple simultaneous specification control scheme. Trajectory tracking results showed that the presented multiple simultaneous specification controller, built experimentally by three PD typed sample controllers, satisfied successfully all required control specifications; rising time, maximum overshoot, steady-state error.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.154.1-154
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• 2001

The paper describes a new type of robot called "artificial liferobot" which is able to learn, make decisions, and behave by itself based on a brain-type computing technique called "artificial brain". The artificial liferobot has self-learning ability from the environment by the interactions between human being and it. The artificial brain makes the artificial liferobot to behave by itself with its intensions like living things as human being. We briefly introduce one attempt of our researches for developing cognitive and behavioral intelligent artificial liferobot in out laboratory. One of our purposes is the development of the artificial liferobot, which plays an Important role in taking care of elderly and infirm people in a rapidly aging society.

• Proceedings of the KTCVS Conference
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• 1993.06a
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• pp.128-128
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• 1993

• Journal of the Korean housing association
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• v.22 no.3
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• pp.113-122
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• 2011

This study aimed to develop AI- (Artificial Intelligence) based thermal control logics and test their performance for identifying the optimal thermal control method in buildings. For this objective, a conventional Two-Position On/Off logic and two AI-based variable logics, which applied ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System), have developed. Performance of each logic was tested in a typical two-story residential building in U.S.A. using the computer simulation incorporating MATLAB and IBPT (International Building Physics Toolbox). In the analysis of the test results, AI-based control logic presented the advanced thermal comfort with stability compared to the conventional logic while they did not show significant energy saving effects. In conclusion, the predictive and adaptive AI-based control logics have a potential to maintain interior air temperature more comfortably, and the findings in this study could be a solid foundation for identifying the optimal thermal control method in buildings.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.485-492
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• 1994

Trajectory tracking control porblems are described for a two-link robot manipulator with artificial rubber muscle actuators. Under the assumption that the so-called independent joint control is applied to the control system, the dynamic model for each link is identified as a linear second-order system with time-lag by the step response. Two control laws such as the feedforward and the computed torque control methods, are experimentally applied for controlling the circular trajectory of an actual robot mainpulator.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1283-1288
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• 2003

This paper proposes an approach to attitude control artificial satellites with jet-engine. The jet-engine produces on-off thrust, which can be modelled as pulse-width-modulated (PWM) function. Therefore, the problem is converted to design a PWM controller and we develop an efficient technique for this purpose using digital redesign. The digital redesign is a converting technique a well-designed analog controller into the equivalent digital one maintaining the property of the original analog control system in the sense of state-matching. The redesigned digital controller is again converted into PWM controller using the equivalent area principle. We show a computer simulation of the attitude control of artificial satellites.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.38-47
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• 1995

A new automatic cardiac output control algorithm for the motor-driven electromechanical total artificial heart(TAH) was developed based on the motor current waveform analysis without using any extra transducer. The basic control requirements of artificial heart can be described in terms of three features : preload sensitivity, afterload insensitivity, and balanced ventricular outputs. In the previous studies, many transducers were utilized to obtain informations of hemodynamic states for the automatic cardiac output control, But such automatic control systems with sensors have had reliability problems. We proposed a new sensorless automatic cardiac output control algorithm providing adequate cardiac output to the time-varying physiological demand without causing right atrial collapse, which is one of the critical problem in an active-filling type device. In-vitro tests were performed on a mock circulation system to evaluate the performance of the developed algorithm and the results show that the new algorithm satisfied the basic control requirements on the cardiac output response and the possibility of application of the developed algorithm to in vivo experiments.