• Title/Summary/Keyword: Instrumentation and control systems

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An LED Lighting with Varying Color Temperature for Emotional Lighting Systems (감성조명 시스템을 위한 색온도 조정 가능한 LED 조명)

  • Liu, Jia;Kim, Hoon;Kim, Hee-Jun
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.522-523
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    • 2008
  • This paper presents an LED lighting which can control its color temperature. It consists of a power factor correction (PFC) circuit, an LED driver, and an LED color control circuit. The proposed system can adjusts the light intensity to obtain a desired color with independently changeable illuminance. The power factor of the PFC circuit is 98%. The LED driver has 90% efficiency at 300mA output current. The output power of the experimented LED lighting is 150 W. The achieved color temperature range was from 3000K to 7500K, and the illumination one was from 500 lux to 1500 lux.

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Development of New Methods for Position Estimation of Underground Acoustic Source Using a Passive SONAR System

  • Jarng, Soon-Suck;Lee, Je-Hyeong;Ahn, Heung-Gu
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.1
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    • pp.69-75
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    • 2000
  • The aim of the work described in this paper is to develop a complex underground acoustic system which detects and localizes the origin of an underground hammering sound using an array of hydrophones located about 100m underground. Three different methods for the sound localization will be presented, a time-delay method, a power-attenuation method and a hybrid method. In the time-delay method, the cross correlation of the signals received from the array of sensors is used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure of the distances of the source from the sensors. In the hybrid method, both informations of time-delays and power-ratios are coupled together to produce better performance of position estimation. A new acoustic imaging technique has been developed for improving the hybrid method. This new acoustic imaging method shows the multi-dimensional distribution of the normalized cost function, so as to indicate the trend of the minimizing direction toward the source location. For each method the sound localization is carried out in three dimensions underground. The distance between the true and estimated origins of the source is 28m for a search area of radius 250m.

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Design of an Elbow Rehabilitation Robot based on Force Measurement and its Force Control (힘측정기반 팔꿈치 재활로봇 설계 및 힘제어)

  • Kim, Han-Sol;Kim, Gab-Soon
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.5
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    • pp.413-420
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    • 2015
  • This paper describes the design of an elbow rehabilitation robot based on force measurement that enables a severe stroke patient confined to their bed to receive elbow rehabilitation exercises. The developed elbow rehabilitation robot was providewitha two-axis force/torque sensor which can detect force Fz and torque Tz, thereby allowing it to measure therotational force (Tz) exerted on the elbow and the signal force Fz which can be used as a safety device. The robot was designed and manufactured for severe stroke patients confined to bed, and the robot program was manufactured to perform flexibility elbow rehabilitation exercises. Asa result of the characteristics test of the developed rehabilitation robot, the device was safely operated while the elbow rehabilitation exercises were performed. Therefore, it is thought that the developed rehabilitation robot can be used for severe stroke patients.

Optimal Control of Induction Motor Using Immune Algorithm Based Fuzzy Neural Network

  • Kim, Dong-Hwa;Cho, Jae-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1296-1301
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    • 2004
  • Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy -neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.

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Intelligent Tuning of PID Controller With Disturbance Rejection Using Bacterial Foraging

  • Kim, Dong-Hwa;Cho, Jae-Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.15-20
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    • 2004
  • In this paper, design approach of PID controller with rejection function against external disturbance in motor control system is proposed using bacterial foraging based optimal algorithm. Up to the present time, PID Controller has been used to operate for AC motor drive because of its implementational advantages in practice and simple structure. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error in the industrial system with disturbance. To design disturbance rejection tuning, disturbance rejection conditions based on H$\_$$\infty$/ are illustrated and the performance of response based on the bacterial foraging is computed for the designed PID controller as ITSE (Integral of time weighted squared error). Hence, parameters of PID controller are selected by bacterial foraging based optimal algorithm to obtain the required response.

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Design of $H_{\infty}$ Controllers for Linear Systems with Input Saturation (입력 포화 특성을 갖는 선형 시스템의 $H_{\infty}$ 제어기 설계)

  • Song, Yong-Heui;Kim, Jin-Hoon
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2040-2042
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    • 2002
  • In this paper, we consider the design of gam scheduled controllers for linear systems with input saturation. We obtain a reachable set and a control gain, which guarantees that the controls are never saturated inside this reachable set and that the $L_2$ gain is minimized, from matrix inequalities. This proposed gain scheduled control gives better performance than that of static control case, and we present the simulation results to show the usefulness of the proposed control.

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Hybrid Intelligent System Using PSO/Bacterial Foraging and PID Controller Tuning

  • Kim Dong-Hwa
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.05a
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    • pp.22-34
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    • 2006
  • o GA-BF approach for improvement of learning and optimization in GA o GA-BF has better response on various test functions o Satisfactory PID controller tuning in AVR, motor vector control systems o Potentially useful in many practically important engineering optimization problems

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Non-PDC Static Output Feedback Control for T-S Fuzzy Systems (T-S 퍼지 시스템에 대한 비병렬분산보상 정적 출력궤환 제어)

  • Jeung, Eun Tae
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.7
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    • pp.496-501
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    • 2016
  • This paper presents a design method of non-parallel distributed compensation (non-PDC) static output feedback controller for continuous- and discrete-time T-S fuzzy systems. The existence condition of static output feedback control law is represented in terms of linear matrix inequalities (LMIs). The proposed sufficient stabilizing condition does not need any transformation matrices and equality constraints and is less conservative than the previous result of [21].

Design of a hybrid fuzzy controller with the optimal auto-tuning method (최적 자동동조 방법에 의한 하이브리드 퍼지제어기의 설계)

  • Oh, Sung-Kwun;Ahn, Tae-Chon;Hwang, Hyung-Soo;Park, Jong-Jin;U, Gwang-Bang
    • Journal of Institute of Control, Robotics and Systems
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    • v.1 no.1
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    • pp.63-70
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    • 1995
  • 퍼지논리제어기는 산업응용에 광범위하게 연구되고 있으며, 계속적으로 사용되고 있다. 그러나 퍼지집합의 조정을 통해 최적규칙을 구축하기 위하여, 시행착오에 의한 매우 능숙한 기술이 요구된다. 이 논문에서는 첫째로, 퍼지논리제어기와 기존의 PID 제어기로 구성된 하이브리드 퍼지제어기를 제안한다. 즉, 시스템의 제어 입력은 퍼지변수로서, 과도상태에서의 FLC출력과 정상상태에서의 PID 출력의 컨벡스(convex) 결합이다. 둘째로, 간략추론법과 개선된 컴플렉스방법을 이용한 강력한 자동동조알고리즘이 퍼지논리제어기의 성능을 자동적으로 개선하기 위하여 사용된다. 이방법은 오차변화율및 제어출력의 제한조건에 의하여, 언어제어규칙, 퍼지계수(scaling factor), PID계수, 하이브리드 퍼지논리제어기의 하중계수의 최적값을 자동적으로 추정한다. 시뮬레이션은 시간지연 플랜트및 하수처리시스템의 활성오니공정과 같은 비선형 플랜트에서 실행되고, 시스템의 성능은 평가지수 ITAE로 평가된다.

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Approximate Dynamic Programming-Based Dynamic Portfolio Optimization for Constrained Index Tracking

  • Park, Jooyoung;Yang, Dongsu;Park, Kyungwook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.19-30
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    • 2013
  • Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.