• Title/Summary/Keyword: Intelligent Control Method

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Intelligent Ship s Steering Gear Control System Using Linguistic Instruction (언어지시에 의한 지능형 조타기 제어 시스템)

  • 박계각;서기열
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.93-97
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    • 2002
  • In this paper, we propose intelligent steering control system that apply LIBL(Linguistic Instruction Based Learning) method to steering system of ship and take the place of process that linguistic instruction such as officer's steering instruction is achieved via ableman. We embody ableman's suitable steering manufacturing model using fuzzy inference rule by specific method of study, and apply LIBL method to present suitable meaning element and evaluation rule to steering system of ship, embody intelligent steering gear control system that respond more efficiently on officer's linguistic instruction. We presented evaluation rule to constructed steering manufacturing model based on ableman's experience, and propose rudder angle for steering system, compass bearing arrival time, meaning element of stationary state, and correct ableman manufacturing model rule using fuzzy inference. Also, we apply LIBL method to ship control simulator and confirmed the effectiveness.

A Study on a Stochastic Nonlinear System Control Using Hyperbolic Quotient Competitive Learning Neural Networks (Hyperbolic Quotient 경쟁학습 신경회로망을 사용한 비선형 확률시스템 제어에 관한 연구)

  • 석진욱;조성원;최경삼
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.346-352
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    • 1998
  • In this paper, we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastic approximation method, it is regarded as a stochastic recursive filter algorithm. In addition, we provide a filtering and control condition for a stochastic nonlinear system, called perfect filtering condition, in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence, the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable. and the proposed neural controller is more efficient than the conventional LQG controller and the canoni al LQ-Neural controller.

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Smart Home Network System Using the Broadband Power Line Communication(BPLC) (광대역 전력선 통신을 이용한 스마트 홈 네트워크 구성에 관한 연구)

  • Yang Hyun-Chang;Sim Kwee-Bo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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    • pp.87-90
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    • 2005
  • The Intelligent Home provides convenient and comfortable living environment by performing automatic control, heating and air-conditioning, ventilation, home appliances control, home robot control, energy management, visitor management security management, internet, heath state monitoring, etc. through wired/ wireless network and device in the household. Along with the presentation of the features of economical broadband power line communication in the network configuration for new and old houses, its improvement method is proposed.

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Synchronousness of Multi-Object Intelligent C System Using Fuzzy Controller (퍼지 제어기를 이용한 다 개체 지능 제어 시스템의 동기화 제어)

  • 문희근;김영탁;공석민;김관형;이상배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.177-180
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    • 2001
  • The subject of this paper is to efficient Pm duty contort for two DC motor synchronousness in the system. Fuzzy controller have been successfully applied to many uncertain and complex industrial plant. So, It adapted fuzzy controller using compositional fuzzy rule so that change PH duty for speed control if the length of destination is different, And for unknow plant, it is the study to make the unknow transfer function system with fuzzy control method. This controller has been successfully applied to Pm duty control for the system synchronousness.

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Sliding Manifold Tuning Method Using Wavelet Neural Network (웨이브릿 신경회로망을 활용한 슬라이딩 매니폴드 조정기법)

  • 홍석우;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.195-198
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    • 2000
  • Sliding mode control method is popularly used for robustness to distrurbance and variance of systems internal parameter. However, one of the serious problem of this method is Chattering which occurs in neighborhood of sliding manifold. Another problem is that we cannot expect robustness before system starts sliding mode. A new tuning method of sliding manifold which changes the parameter of sliding manifold dynamically using Wavelet Neural Network is proposed in this paper. We can expect the better performance in sliding mode control by the wavelet neural networks excellent property of approximating arbitrary function for multi-resolution analysis and decrease chattering drastically.

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Sensorless Speed Control of Induction motor using the Intelligent Speed Estimator (지능형 속도 추정기를 이용한 유도전동기의 센서리스 속도제어)

  • Park, Jin-Su;Choi, Sung-Dae;Kim, Sang-Hoon;Yoon, Kwang-Ho;Ban, Gi-Jong;Nam, Moon-Hyon;Kim, Lark-Kyo
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.660-662
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    • 2004
  • This paper proposes an Intelligent Speed Estimator in order to realize the speed-sensorless vector control of an induction motor. Intelligent Speed Estimator used Model Reference Adaptive System which has Fuzzy-Neural adaptive mechanism as Speed Estimation method. The Intelligent Speed Estimator estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. The Intelligent Speed Estimator reduces the error of the rotor flux between the voltage flux model and the current flux model using the error and the change of error as input of the Estimator. The computer simulation is executed to verify the propriety and the effectiveness of the proposed speed estimator.

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Application of Neural Network for the Intelligent Control of Computer Aided Testing and Adjustment System (자동조정기능의 지능형제어를 위한 신경회로망 응용)

  • 구영모;이승구;이영민;우광방
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.1
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    • pp.79-89
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    • 1993
  • This paper deals with a computer aided control of an adjustment process for the complete electronic devices by means of an application of artificial neural network and an implementation of neuro-controller for intelligent control. Multi-layer neural network model is employed as artificial neural network with the learning method of the error back propagation. Information initially available from real plant under control are the initial values of plant output, and the augmented plant input and its corresponding plant output at that time. For the intelligent control of adjustment process utilizing artificial neural network, the neural network emulator (NNE) and the neural network controller(NNC) are developed. The initial weights of each neural network are determined through off line learning for the given product and it is also employed to cope with environments of the another product by on line learning. Computer simulation, as well as the application to the real situation of proposed intelligent control system is investigated.

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Development of Intelligent Landscape Lighting Power Control and Monitoring System with Solar Cell Generator Equipment (태양광발전설비와 연계한 지능형 경관조명 전력제어 및 모니터링 시스템의 개발)

  • Kim, Dong-Wan;Park, Sung-Won;Kim, Hyung-Su
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.60 no.2
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    • pp.99-104
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    • 2011
  • In this paper, the intelligent landscape lighting power control and monitoring system with solar sell generator equipment is proposed. The first, the intelligent landscape lighting power controller is designed using the fuzzy logic control method. And the fuzzy logic controller is used to save power consumption for various reference intensity of the illumination. The second, the GUI monitoring system is presented. It has control and display faculty. And the practical experiment device is used to evaluate the performance criteria of the proposed intelligent landscape lighting power control system with the solar cell power generation equipment. From the experiment results, we present the property of proposed fuzzy controller such as steady state error, the tracking and power consumption characteristic for the reference intensity of illumination. And also we show the superiority of power control as well as the characteristic of GUI monitoring system in the proposed system.

Development of the Broadband PLC Home Controller using JINI Surrogate

  • Kim, Yong-Seok;Kim, Hee-Sun;Lee, Chang-Goo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1563-1567
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    • 2005
  • The Home network system means that information appliances, Home PCs, etc., using wired or wireless network method enable to control and share with peripheral devices such as internet, shared data, a scanner and a printer, and it is networking solution, which intelligent communication will be possible as the system which can do a remote control such as TV Set, refrigerators, air conditioners, DVD players, digital camcorders based on external network using an internet, a potable information terminal and a mobile phone whenever, wherever and freely. In this study, the home network interface solution is used one of the wired network standards, PLC (Power-Line Communication) technology, so we can construct of intelligent home network's home controller without re-build a network at home. On keeping with current waves of thought, we will focus on a home controller development with great interest which is enabled to do an effective managed control, applying intelligent home network technology which can be new paradigm like a cyber apartment.

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Design of neuro-fuzzy for robust control of induction motor (유도전동기의 강인 제어를 위한 뉴로-퍼지 설계)

  • 송윤재;강두영;김형권;안태천
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.454-457
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    • 2004
  • In this paper, control method proposed for effective speed control of the induction motor indirect vector control. For the induction motor drive, indirect vector control scheme that controls torque current and flux current of the stator current independently so that it can have improved dynamics. Also, neuro-fuzzy algorithm employed for torque current control in order to optimal speed control The proposed neuro-fuzzy algorithm can be applied to the precise speed control of an induction motor drive system or the field of any other power systems.

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