• 제목/요약/키워드: model-based method

검색결과 19,606건 처리시간 0.041초

구조물의 연결부에서 전달함수합성법을 이용한 동응력 해석 (Dynamic Stress Analysis of Structural Connection using FRF-based Substructuring Method)

  • 공태식;김찬묵;이두호;서세영
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 춘계학술대회논문집
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    • pp.1195-1201
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    • 2002
  • Researches on the FRF-based substructuring method have been mainly focused on vibratory response analysis. Present study Is concerned about the application of the method to the dynamic stress analysis of a air-conditioner compressor mounting bracket in a passenger car. This is performed by using reaction forces that can be obtained by the FRF-based substructuring method. The air-conditioner system, composed of a compressor and bracket, Is analyzed by using the FRF-based substructuring method. The experimental and numerical FRFs are combined to calculate the system responses and reaction forces at the connection point. The dynamic reaction forces plugged into the bracket FE model to compute the stresses of the bracket Dynamic strains by the present method are compared with those from strain-gage test for bracket system on shaker. The comparison shows possibility of practical usage of the method for the real problem

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기동 표적 추적을 위한 DNA 코딩 기반 상호작용 다중모델 기법 (A DNA Coding-Based Interacting Multiple Model Method for Tracking a Maneuvering Target)

  • 이범직;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.87-91
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    • 2002
  • The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, a DNA coding-based interacting multiple model (DNA coding-based IMM) method is proposed. The proposed method can overcome the mathematical limits of conventional methods by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive IMM algorithm and the GA-based IMM method in computer simulations.

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하이브리드 방식에 의한 미시적 부하모델링 (Component-Based Load Modeling Updated by Hybrid Technique)

  • 지평식
    • 대한전기학회논문지:전력기술부문A
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    • 제52권3호
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    • pp.179-182
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    • 2003
  • Component-based method for load model not only should include the performances of the load components, but also should take into consideration the core losses of transformers, the line losses and the capacitor banks. Especially, capacitor bank affects the accuracy of reactive load model in load modeling. But it is difficult to identify actual reactive powers of capacitor banks in power system for load modeling. This research improves the component-based modeling method including uncertain capacitor bank. The proposed method is hybrid technique, which adds the measurement-based method to the existing component-based method for reliable information of capacitor band. The results of case studies were presented to verify the validity of the proposed method.

A Model reference adaptive speed control of marine diesel engine by fusion of PID controller and fuzzy controller

  • Yoo, Heui-Han
    • Journal of Advanced Marine Engineering and Technology
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    • 제30권7호
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    • pp.791-799
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    • 2006
  • The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

Implementation of Q-Tensor Model into 3-D Finite Element Method (FEM) Numerical Solver

  • Shin, Woo-Jung;Yoon, Hyung-Jin;Won, Tae-Young
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권1호
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    • pp.509-512
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    • 2007
  • In this paper, we report our successful implementation of Q tensor model in threedimensional finite element method (FEM) simulator. The 3D-FEM Q tensor-model-based simulation revealed that the spaly-to-bend transition occurs only at 4 V while the vector-model based FEM solver provides an erroneous transition voltage of 8 V.

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확률모델 불확실성을 고려한 구조물의 신뢰도 기반 최적설계 - 제2편: 강인 성능 평가 (Reliability-based Structural Design Optimization Considering Probability Model Uncertainties - Part 2: Robust Performance Assessment)

  • 옥승용;박원석
    • 한국안전학회지
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    • 제27권6호
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    • pp.115-121
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    • 2012
  • This paper, being the second in a two-part series, presents the robust performance of the proposed design method which can enhance a reliability-based design optimization(RBDO) under the uncertainties of probabilistic models. The robust performances of the solutions obtained by the proposed method, described in the Part 1, are investigated through the parametric studies. A 10-bar truss example is considered, and the uncertain parameters include the number of data observed, and the variations of applied loadings and allowable stresses. The numerical results show that the proposed method can produce a consistent result despite of the large variations in the parameters. Especially, even with the relatively small data set, the analysis results show that the exact probabilistic model can be successfully predicted with optimized design sections. This consistency of estimating appropriate probability model is also observed in the case of the variations of other parameters, which verifies the robustness of the proposed method.

Probabilistic bearing capacity assessment for cross-bracings with semi-rigid connections in transmission towers

  • Zhengqi Tang;Tao Wang;Zhengliang Li
    • Structural Engineering and Mechanics
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    • 제89권3호
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    • pp.309-321
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    • 2024
  • In this paper, the effect of semi-rigid connections on the stability bearing capacity of cross-bracings in steel tubular transmission towers is investigated. Herein, a prediction method based on the hybrid model which is a combination of particle swarm optimization (PSO) and backpropagation neural network (BPNN) is proposed to accurately predict the stability bearing capacity of cross-bracings with semi-rigid connections and to efficiently conduct its probabilistic assessment. Firstly, the establishment of the finite element (FE) model of cross-bracings with semi-rigid connections is developed on the basis of the development of the mechanical model. Then, a dataset of 7425 samples generated by the FE model is used to train and test the PSO-BPNN model, and the accuracy of the proposed method is evaluated. Finally, the probabilistic assessment for the stability bearing capacity of cross-bracings with semi-rigid connections is conducted based on the proposed method and the Monte Carlo simulation, in which the geometric and material properties including the outer diameter and thickness of cross-sections and the yield strength of steel are considered as random variables. The results indicate that the proposed method based on the PSO-BPNN model has high accuracy in predicting the stability bearing capacity of cross-bracings with semi-rigid connections. Meanwhile, the semi-rigid connections could enhance the stability bearing capacity of cross-bracings and the reliability of cross-bracings would significantly increase after considering semi-rigid connections.

사용자 데모를 이용한 관계적 개체 기반 정책 학습 (Learning Relational Instance-Based Policies from User Demonstrations)

  • 박찬영;김현식;김인철
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제37권5호
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    • pp.363-369
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    • 2010
  • 데모-기반 학습은 사용자가 직접 작업을 시연함으로써 로봇에게 쉽게 새로운 작업지식을 가르칠 수 있다는 장점이 있다. 하지만 기존의 많은 데모-기반 학습법들은 상태공간과 정책들을 표현하기 위해 속성-값 벡터 모델을 이용하였다. 속성-값 벡터 모델의 제한성으로 인해, 이들은 학습과정의 효율성도 낮고 학습된 정책의 재사용성도 낮았다. 본 논문에서는 기존의 속성-값 모델 대신 관계적 모델을 이용하는 새로운 데모-기반 작업 학습법을 제안한다. 이 방법에서는 사용자 데모 기록에서 추출한 훈련 예들에 관계적 개체-기반 학습법을 적용함으로써, 동일 작업영역내의 다른 유사한 작업들에도 활용하기 용이한 관계적 개체-기반 정책을 유도한다. 이 관계적 정책은 (상태, 목표) 쌍으로 표현되는 임의의 한 상황에 대해 이것에 대응하는 하나의 실행동작을 결정해주는 역할을 한다. 본 논문에서는 데모-기반 관계적 정책 학습법에 대해 자세히 소개한 후, 로봇 시뮬레이터를 이용한 실험을 통해 이 학습법의 효과를 분석해본다.

이중 지수 점프확산 모형하에서의 마코브 체인을 이용한 아메리칸 옵션 가격 측정 (Valuation of American Option Prices Under the Double Exponential Jump Diffusion Model with a Markov Chain Approximation)

  • 한규식
    • 대한산업공학회지
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    • 제38권4호
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    • pp.249-253
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    • 2012
  • This paper suggests a numerical method for valuation of American options under the Kou model (double exponential jump diffusion model). The method is based on approximation of underlying asset price using a finite-state, time-homogeneous Markov chain. We examine the effectiveness of the proposed method with simulation results, which are compared with those from the conventional numerical method, the finite difference method for PIDE (partial integro-differential equation).

Design of T-S Fuzzy Model based Adaptive Fuzzy Observer and Controller

  • Ahn, Chang-Hwan
    • 조명전기설비학회논문지
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    • 제23권11호
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    • pp.9-21
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    • 2009
  • This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.