• Title/Summary/Keyword: Fuzzy Control System

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Home Network Electrical Appliance Control With The UPnP Expansion

  • Cho, Kyung-Hee;Lee, Sung-Joo;Chung, Hyun-Sook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.2
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    • pp.127-131
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    • 2007
  • The control of electrical appliances residing in the home network can be accomplished via Internet with the UPnP expansion without modifying an existing UPnP. In this paper, we propose the Internet Gateway that consists of an UPnP IGD(Internet Gateway Device) DCP(Device Control Protocol) and an UPnP Bridge as a system to control electrical appliances of home network. UPnP IGD DCP is to enable the configurable initiation and sharing of Internet connections as well as assuring advanced connection-management features and management of host configuration service. It also supports transparent Internet access by non-UPnP-certified devices. UPnP Bridge searches for local home network devices by sending control messages, while control point of UPnP Bridge looks up devices of interest on the Internet, subsequently furnishing the inter-networking controlling among devices which belong to different home network systems. With our approach, devices on one home network can control home electrical appliances on the other home network via Internet through IGD DCP with control commands of UPnP.

Optimum design of a sliding mode control for seismic mitigation of structures equipped with active tuned mass dampers

  • Eliasi, Hussein;Yazdani, Hessam;Khatibinia, Mohsen;Mahmoudi, Mehdi
    • Structural Engineering and Mechanics
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    • v.81 no.5
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    • pp.633-645
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    • 2022
  • The active tuned mass damper (ATMD) is an efficient and reliable structural control system for mitigating the dynamic response of structures. The inertial force that an ATMD exerts on a structure to attenuate its otherwise large kinetic energy and undesirable vibrations and displacements is proportional to its excursion. Achieving a balance between the inertial force and excursion requires a control law or feedback mechanism. This study presents a technique for the optimum design of a sliding mode controller (SMC) as the control law for ATMD-equipped structures subjected to earthquakes. The technique includes optimizing an SMC under an artificial earthquake followed by testing its performance under real earthquakes. The SMC of a real 11-story shear building is optimized to demonstrate the technique, and its performance in mitigating the displacements of the building under benchmark near- and far-fault earthquakes is compared against that of a few other techniques (proportional-integral-derivative [PID], linear-quadratic regulator [LQR], and fuzzy logic control [FLC]). Results indicate that the optimum SMC outperforms PID and LQR and exhibits performance comparable to that of FLC in reducing displacements.

Design of Neuro-Fuzzy LED Emotional Lighting System for Concentration and Resting Situations in Indoor Environment (실내 환경 집중 및 휴식상황에서의 뉴로-퍼지를 통한 LED 감성조명 시스템 설계)

  • Kang, Eun-Yeong;Kim, Hyo-Jun;Park, Keon-Jun;Kim, Young-Kab
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.3
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    • pp.558-566
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    • 2015
  • LED, the next-generation light source, rapidly develops and has advantages of low power, high efficiency, and long life. Accordingly, an interest in lightings by using LED rises. If emotional lighting is implemented by using LED, all colors can be represented by using 3 primary colors of light, differently from the conventional single-color lighting. LED emotional lightings which can control human emotions continue to be developed thanks to these advantages. This study was conducted to design an algorithm for expressing LED emotional lighting in line with the situation and temperature by extracting colors for concentration and resting situations in indoor environment and mixing them with colors of the temperature felt by user. The LED emotional lighting designed with a neuro-fuzzy system was found to have effects on user's emotions during concentration and resting.

On an Algorithm for the Assessment of Collision Risk among Multiple Ships based on AIS (AIS 기반 다중선박 충돌 위험도 추정 알고리즘에 관한 연구)

  • Son, Nam-Sun;Oh, Jae-Yong;Kim, Sun-Young
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2009.10a
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    • pp.62-63
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    • 2009
  • A monitoring system of collision risk among multiple ships is newly-designed in order to reduce human error and make vessel traffic control more effective. By using AIS data as ships' navigational information, an estimation algorithm of collision risk among multiple ships is newly-designed. To consider ships' course of now and future, collision risks of multiple ships can be calculated by using fuzzy algorithm. To test the performance of new algorithm, replay simulations are carried out on actual AIS data collected from VTS center of Ulsan harbor in Korea. The AIS data include 25 ships' information for two hours. In this paper, the features of newly-designed estimation algorithm of collision risk and the results of replay simulation are discussed.

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Performance Improvement of Intelligent Firefignting Control System for a Ship using Fuzzy Database (선박에서 퍼지 데이터베이스를 이용한 지능형 화재진압통제시스템의 성능 개선)

  • 현우석;김용기
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.340-343
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    • 2000
  • 본 논문에서는 선박에서 퍼지 데이터베이스를 이용하여 지능형 화재진압통제시스템의 성능을 개선시키는 방법에 대하여 논의하였다. 규칙과 사례가 통합된 화재진압통제 전문가시스템(C-FFES)에서는 사례기반 추론을 하기 위한 사례베이스가 일반적인 데이터베이스로 구성되어 있어서, 이전에 화재가 발생했던 사례와 현재의 사례가 유사한지를 구별하기가 쉽지 않은 문제점을 지니고 있다. 제안하는 시스템에서는 예외적인 상황에서 화재가 발생하는 사례를 퍼지데이터베이스로 구성하고, 현 상황과 예외적인 상황에서 화재가 발생하는 사례를 조회하기 위하여 퍼지 유사도 개념을 적용하여 현재 입력된 사례와 가장 유사한 사례가 조회될 수 있도록 하였다. 또한 기존의 규칙 기반 FFES(Fire Fighting Expert System), 사례기반 추론에 의해 확장된 C-FFES(Combined-Fire Fighting Expert System) 그리고 제안하는 A-FFES(Advanced Fire fighting Expert System)를 비교를 통해, 제안하는 A-FFES가 화재탐지율을 향상시킴을 보였다.

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Observer-based sampled-data controller of linear system for the wave energy converter

  • Koo, Geun-Bum;Park, Jin-Bae;Joo, Young-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.4
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    • pp.275-279
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    • 2011
  • In this paper, an observer-based sampled-data controller of linear system is proposed for the wave energy converter. Based on the sampled-data observer, the controller is design. In the closed-loop system with controller, it obtains the norm inequality between the continuous-time state variable and the discrete-time one. Using the norm inequality, sufficient condition is derived for the asymptotic stability of the closed-loop system and formulated in terms of linear matrix inequality. Finally, the wave energy converter simulation is provided to verify the effectiveness of the proposed technique.

Design of STATCOM Stabiliser for Improving Power System Stability (전력계통 안정도 향상을 위한 STATCOM 안정화 장치 설계)

  • Lee, Seok-Oh;Jung, Young-Min;Mun, Kyeong-Jun;Hwang, Gi-Hyun;Park, June-Ho;Lee, Jeong-Kwan
    • Proceedings of the KIEE Conference
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    • 2001.07a
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    • pp.149-151
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    • 2001
  • This paper proposes the design of STATCOM(static synchronous compensator) stabilizer for improving power system stability using fuzzy logic controller(FLC). The STATCOM DC voltage regulator contributes negative damping to the power system as the installation of STATCOM DC voltage regulator. STATCOM stabiliser is superimposed on the AC voltage regulator to compensate the negative damping effect. To evaluate usefulness of the proposed method, we perform the nonlinear simulation on a single-machine infinite bus system. As results of the simulations, the proposed method shows better control performance than PI controller in terms of damping effects.

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Evolvable Neural Networks Based on Developmental Models for Mobile Robot Navigation

  • Lee, Dong-Wook;Seo, Sang-Wook;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.176-181
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    • 2007
  • This paper presents evolvable neural networks based on a developmental model for navigation control of autonomous mobile robots in dynamic operating environments. Bio-inspired mechanisms have been applied to autonomous design of artificial neural networks for solving practical problems. The proposed neural network architecture is grown from an initial developmental model by a set of production rules of the L-system that are represented by the DNA coding. The L-system is based on parallel rewriting mechanism motivated by the growth models of plants. DNA coding gives an effective method of expressing general production rules. Experiments show that the evolvable neural network designed by the production rules of the L-system develops into a controller for mobile robot navigation to avoid collisions with the obstacles.

Smoothing Output Power Variations of Isolated Utility Connected Multiple PV Systems by Coordinated Control

  • Datta, Manoj;Senjyu, Tomonobu;Yona, Atsushi;Sekine, Hideomi;Funabashi, Toshihisa
    • Journal of Power Electronics
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    • v.9 no.2
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    • pp.320-333
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    • 2009
  • A Photovoltaic (PV) system's power output varies with the change of climate. Frequency deviations, tie line voltage swings are caused by the varying PV power when large PV power from several PV systems is fed in the utility. In this paper, to overcome these problems, a simple coordinated control method for smoothing the variations of combined PV power from multiple PV systems is proposed. Here, output power command is formed in two steps: central and local. Fuzzy control is used to produce the central smoothing output power command considering insolation, variance of insolation and absolute average of frequency deviation. In local step, a simple coordination is kept between the central power command and the local power commands by producing a common tuning factor. Power converters are used to achieve the same output power as local command power employing PI control law for each of the PV generation systems. The proposed method is compared with the method where conventional Maximum Power Point Tracking (MPPT) control is used for each of the PV systems. Simulation results show that the proposed method is effective for smoothing the output power variations and feasible to reduce the frequency deviations of the power utility.

Experimental Studies of Real- Time Decentralized Neural Network Control for an X-Y Table Robot

  • Cho, Hyun-Taek;Kim, Sung-Su;Jung, Seul
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.3
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    • pp.185-191
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    • 2008
  • In this paper, experimental studies of a neural network (NN) control technique for non-model based position control of the x-y table robot are presented. Decentralized neural networks are used to control each axis of the x-y table robot separately. For an each neural network compensator, an inverse control technique is used. The neural network control technique called the reference compensation technique (RCT) is conceptually different from the existing neural controllers in that the NN controller compensates for uncertainties in the dynamical system by modifying desired trajectories. The back-propagation learning algorithm is developed in a real time DSP board for on-line learning. Practical real time position control experiments are conducted on the x-y table robot. Experimental results of using neural networks show more excellent position tracking than that of when PD controllers are used only.