• Title/Summary/Keyword: Fuzzy systems modeling

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Design and Implementation of Tele-operation system based on the Haptic Interface

  • Lee, Jong-Bae;Lim, Joon-Hong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.161-165
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    • 2003
  • In this paper, we investigate the issues on the design and implementation of tele-operation system based on the haptic interface. Here, the 3-DOF haptic device and the X-Y-Z stage are employed as master controller and slave system respectively. For this master-slave system, the force feedback algorithm, the modeling of virtual environments and the control method of X-Y-Z stage are presented. In this paper, internet network is used for data communication between master and slave. We construct virtual environment of the real convex surface from the force-feedback in controlling the X-Y-Z stage and measuring the force applied by the 3-DOF haptic device.

FMFNN Modeling of the Tire Characteristics for Ground Vehicle Control (차량 제어를 위한 타이어 특성의 퍼지 소속 함수 신경망 모델링)

  • 박명관;서일홍
    • Journal of the Korean Institute of Intelligent Systems
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    • v.6 no.2
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    • pp.57-71
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    • 1996
  • 차량 모델 비선형성의 주된 요인중 하나는 타이어의 비선형성이라고 할 수 있다. 타이어 모델도 간편화하기 위해 선형화된 타이어 모델을 적용할 경우에 저속 주행 또는 고속 주행이라고도 조향각이 적을 때는 문제가 없지만, 급격한 가감속과 과도한 조향각을 주었을 때는 타이어 미끄럼 각(Tire Slip Angle)이 급격히 변화되므로 선형화 된 타이어 모텔을 적용하지 못하게 된다. 그러므로 타이어와 지면 사이의 물리적 현상을 자세히 표현할 수 있는 비선형 타이어 모델을 적용하지 못하게 된다. 그러므로 타이어와 지면 사이의 물리적 현상을 자세히 표현할 수 있는 비선형 타이어 모델이 요구되어진다. 실험적 모델은 실제 차량의 실험 데이터를 바탕으로 커브 피팅(Curve Fitting)하여 타이어의 동특성을 표현하도록 모델링 하므로서 모델의 정확도를 높일 수 있는 반면 요구하는 계수들이 많아지게 되어 계산량이 증가되는 단점이 있다. 기존의 타이어 모델 연구 결과에 대해 분석하고, 관측 자료들을 바탕으로 FMFNN(Fuzzy Membership Function based Neural Network)을 이용한 함수 근사화로서 타이어 횡축력과 종축력의 모델링 방법을 제안하였다.

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Asynchronous Behavior Control Algorithm of the Swarm Robot for Surrounding Intruders (군집 로봇의 침입자 포위를 위한 비동기 행동 제어 알고리즘)

  • Kim, Jong-Seon;Joo, Young-Hoon
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.9
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    • pp.812-818
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    • 2012
  • In this paper, we propose an asynchronous behavior control algorithm of the swarm robot for surrounding intruders when detected an intruder in a surveillance environment. The proposed method is divided into three parts: First, we proposed the method for the modeling of a state of the swarm robot. Second, we proposed an asynchronous behavior control algorithm for the surrounding an intruder by the swarm robot. Third, we proposed a control method for the collision avoidance with the swarm robot. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

Specialized Product-Line Development Methodology for Developing the Embedded System

  • Hong Ki-Sam;Yoon Hee-Byung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.3
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    • pp.268-273
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    • 2005
  • We propose the specialized product-line development methodology for developing the embedded system of an MSDFS (Multi Sensor Data Fusion System : called MSDFS). The product-line methodology provides a simultaneous design between software and hardware, high level reusability. However this is insufficient in requirement analysis stage due to be focused on software architecture, detailed design and code. Thus we apply the business model based on IDEF0 technique to traditional methodology. In this paper, we describe the processes of developing Core-Asset, which are requirement analysis, feature modeling, validation. The proposed model gives the efficient result for eliciting features, and ensures the high level reusability of modules performing on embedded system.

Intelligent Digital Decentralized Control System for Smart Space (스마트 스페이스 구축을 위한 지능형 디지털 분산 제어 시스템 개발)

  • Joo, Young-Hoon
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.1
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    • pp.54-59
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    • 2006
  • The smart space is composed of the wire and/or wireless network, multi-sensor-based environment, and many various controllers. For the smart space, this paper presents a new design method of multirate digital decentralized controller using the intelligent digital redesign technique. In specific, the proposed method is based on the delta-operator and the multirate sampling and takes the form of the LMIs. To shows the feasibility of the suggested method, the computer simulations for Heating, ventilating, and ai. conditioning (HVAC) system are provided.

A Study on the Advancement Structure Model of Maritime Safety Information System(GICOMS) using FSM (FSM을 이용한 해양안전정보시스템의 고도화 구조모델 연구)

  • Ryu, Young-Ha;Park, Kark-Gyei;Kim, Hwa-Young
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.3
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    • pp.337-342
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    • 2014
  • This paper is aims to build the advancement structural model of GICOMS through identification of required system and improvement for implementation of e-Navigation. We derived nine improvement subject for model of advanced GICOMS through the analysis of problems for GICOMS and brainstorming with expert in the maritime safety. And we analyzed the structure of nine improvement subject using by FSM(Fuzzy Structural Modeling) method, and proposed a structural model that to grasp the correlation between elements. As a result, we found out that "advancement of GICOMS" is the final goal, and "improvement a system of information production", "improvement a scheme of information providing", "linkage between GICOMS and VTS" and "building global networks for safety cooperation" are located lowest level. Especially, "advancement of GICOMS" is influenced by "advancement function of VMS" and "Activation of usage" on middle level. We suggested that utilizing state-of-the-art IT facilities, equipment and expertise to improve and enhance the user-centered transition such as maritime workers for advancement of GICOMS based on proposed structure model.

Effects of infill walls on RC buildings under time history loading using genetic programming and neuro-fuzzy

  • Kose, M. Metin;Kayadelen, Cafer
    • Structural Engineering and Mechanics
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    • v.47 no.3
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    • pp.401-419
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    • 2013
  • In this study, the efficiency of adaptive neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) in predicting the effects of infill walls on base reactions and roof drift of reinforced concrete frames were investigated. Current standards generally consider weight and fundamental period of structures in predicting base reactions and roof drift of structures by neglecting numbers of floors, bays, shear walls and infilled bays. Number of stories, number of bays in x and y directions, ratio of shear wall areas to the floor area, ratio of bays with infilled walls to total number bays and existence of open story were selected as parameters in GEP and ANFIS modeling. GEP and ANFIS have been widely used as alternative approaches to model complex systems. The effects of these parameters on base reactions and roof drift of RC frames were studied using 3D finite element method on 216 building models. Results obtained from 3D FEM models were used to in training and testing ANFIS and GEP models. In ANFIS and GEP models, number of floors, number of bays, ratio of shear walls and ratio of infilled bays were selected as input parameters, and base reactions and roof drifts were selected as output parameters. Results showed that the ANFIS and GEP models are capable of accurately predicting the base reactions and roof drifts of RC frames used in the training and testing phase of the study. The GEP model results better prediction compared to ANFIS model.

A Biological Reaction Modeling in Sewage Water Treatment Systems (하수처리장에서 생물학적 반응 특성에 대한 모델)

  • 이진락;양일화;이해영
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.15 no.4
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    • pp.37-42
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    • 2001
  • This paper resents a biological reaction model of describing processing features in treating wastewater via activated sludge A proposed model is designed by combining fuzzy rules investigating several elements which have influence on variables to be supervised BOD and SS are suggested as common variables in input and output variables, and O$_2$quantity is closed as input variable. We chose triangular type membership functions for input variables and determined the grades in each membership function based upon process data According to simulation result to show the validity of proposed model, fuzzy model's outputs give almost similar data to process output under same input conditions.

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Intrusion Detection System Modeling Based on Learning from Network Traffic Data

  • Midzic, Admir;Avdagic, Zikrija;Omanovic, Samir
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5568-5587
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    • 2018
  • This research uses artificial intelligence methods for computer network intrusion detection system modeling. Primary classification is done using self-organized maps (SOM) in two levels, while the secondary classification of ambiguous data is done using Sugeno type Fuzzy Inference System (FIS). FIS is created by using Adaptive Neuro-Fuzzy Inference System (ANFIS). The main challenge for this system was to successfully detect attacks that are either unknown or that are represented by very small percentage of samples in training dataset. Improved algorithm for SOMs in second layer and for the FIS creation is developed for this purpose. Number of clusters in the second SOM layer is optimized by using our improved algorithm to minimize amount of ambiguous data forwarded to FIS. FIS is created using ANFIS that was built on ambiguous training dataset clustered by another SOM (which size is determined dynamically). Proposed hybrid model is created and tested using NSL KDD dataset. For our research, NSL KDD is especially interesting in terms of class distribution (overlapping). Objectives of this research were: to successfully detect intrusions represented in data with small percentage of the total traffic during early detection stages, to successfully deal with overlapping data (separate ambiguous data), to maximize detection rate (DR) and minimize false alarm rate (FAR). Proposed hybrid model with test data achieved acceptable DR value 0.8883 and FAR value 0.2415. The objectives were successfully achieved as it is presented (compared with the similar researches on NSL KDD dataset). Proposed model can be used not only in further research related to this domain, but also in other research areas.

A Design of Reference Model Following Fuzzy Control System for Boiler-Turbine Equipment (보일러-터빈 설비에 대한 기준모델 추종 퍼지 제어시스템의 설계)

  • 정호성;황창선;황현준
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.11 no.4
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    • pp.82-91
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    • 1997
  • In this paper, a design method of the boiler-turbine control system in the coal fired power plant is proposed. We need to control electric output and drum pressure and water level in drum to guarantee stable operation and save energy for generating electricity and decrease air pollution in the boiler-turbine system. This boiler-turbine control system is composed of reference model part and model following part. The multivariable boiler-turbine system is separated into 3 SISO(Single Input Single Output) systems applying the concept of relative gain matrix. Each 3 reference models for separated boiler-turbine system are composed of 1st order nominal plant and hysteresis integral control system and they make good dy¬namic response with no overshoot and fast rising time. Each fuzzy controller to follow as close as possible to the response of each reference model is designed. The robustness and the good tracking property can be achieved using 5150 fuzzy controllers when there are modeling errors, disturbances and parameter pertur¬bations. The effectiveness of the proposed design method is verified through simulations.

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