• 제목/요약/키워드: State-Space Method

검색결과 1,158건 처리시간 0.037초

Recursive State Space Model Identification Algorithms Using Subspace Extraction via Schur Complement

  • Takei, Yoshinori;Imai, Jun;Wada, Kiyoshi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.525-525
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    • 2000
  • In this paper, we present recursive algorithms for state space model identification using subspace extraction via Schur complement. It is shown that an estimate of the extended observability matrix can be obtained by subspace extraction via Schur complement. A relationship between the least squares residual and the Schur complement matrix obtained from input-output data is shown, and the recursive algorithms for the subspace-based state-space model identification (4SID) methods are developed. We also proposed the above algorithm for an instrumental variable (IV) based 4SID method. Finally, a numerical example of the application of the algorithms is illustrated.

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자기부상열차-가이드웨이 통합 시스템의 동적 특성 (Dynamic Response of Coupled Maglev Train and Guideway System)

  • 공은호;강부병;나성수
    • 한국소음진동공학회논문집
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    • 제21권2호
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    • pp.137-145
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    • 2011
  • This study is proposed to develop a numerical interaction model of the magnetically levitated(maglev) train and guideway. For this purpose, equation of motion for 6-DOF vehicle model, EMS, guideway and guideway irregularity are derived as the state-space equation. In order to solve the state space equations, the present work was performed via matlab simulation using Runge-Kutta method. Through the simulation, the effect of dynamic response of maglev system to different vehicle speeds, guideway rigidity(EI) and masses is investigated.

Modeling and fast output sampling feedback control of a smart Timoshenko cantilever beam

  • Manjunath, T. C.;Bandyopadhyay, B.
    • Smart Structures and Systems
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    • 제1권3호
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    • pp.283-308
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    • 2005
  • This paper features about the modeling and design of a fast output sampling feedback controller for a smart Timoshenko beam system for a SISO case by considering the first 3 vibratory modes. The beam structure is modeled in state space form using FEM technique and the Timoshenko beam theory by dividing the beam into 4 finite elements and placing the piezoelectric sensor/actuator at one location as a collocated pair, i.e., as surface mounted sensor/actuator, say, at FE position 2. State space models are developed for various aspect ratios by considering the shear effects and the axial displacements. The effects of changing the aspect ratio on the master structure is observed and the performance of the designed FOS controller on the beam system is evaluated for vibration control.

CELL STATE SPACE ALGORITHM AND NEURAL NETWORK BASED FUZZY LOGIC CONTROLLER DESIGN

  • Aao;Ding, Gen-Ya
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.972-974
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    • 1993
  • This paper presents a new method to automatically design fuzzy logic controller(FLC). The main problems of designing FLC are how to optimally and automatically select the control rules and the parameters of membership function (MF). Cell state space algorithms (CSS), differential competitive learning (DCL) and multialyer neural network are combined in this paper to solve the problems. When the dynamical model of a control process is known. CSS can be used to generate a group of optimal input output pairs(X, Y) used by a controller. The(X, Y) then can be used to determine the FLC rules by DCL and to determine the optimal parameters of MF by DCL and to determine the optimal parameters of MF by multilayer neural network trained by BP algorithm.

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The hybrid uncertain neural network method for mechanical reliability analysis

  • Peng, Wensheng;Zhang, Jianguo;You, Lingfei
    • International Journal of Aeronautical and Space Sciences
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    • 제16권4호
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    • pp.510-519
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    • 2015
  • Concerning the issue of high-dimensions, hybrid uncertainties of randomness and intervals including implicit and highly nonlinear limit state function, reliability analysis based on the hybrid uncertainty reliability mode combining with back propagation neural network (HU-BP neural network) is proposed in this paper. Random variables and interval variables are as input layer of the neural network, after the training and approximation of the neural network, the response variables are obtained through the output layer. Reliability index is calculated by solving the optimization model of the most probable point (MPP) searching in the limit state band. Two numerical cases are used to demonstrate the method proposed in this paper, and finally the method is employed to solving an engineering problem of the aerospace friction plate. For this high nonlinear, small failure probability problem with interval variables, this method could achieve a good analysis result.

Euclidean 거리연산자와 결합된 상태공간 기법에 의한 영상추출 (A Study on the Extraction of Feature by State-Space Concept with Euclidean Distance Operator)

  • 최갑석;윤동한
    • 대한전자공학회논문지
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    • 제23권6호
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    • pp.846-852
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    • 1986
  • An efficient and reliable method for the extraction of features is presented. The method utilizes by a state technique with Euclidean distance operator. The proposed method is compared with the Sobel Operator. Simulation results show that our method performs as well as the Sobel operator.

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Validation of Generalized State Space Averaging Method for Modeling and Simulation of Power Electronic Converters for Renewable Energy Systems

  • Rimmalapudi, Sita R.;Williamson, Sheldon S.;Nasiri, Adel;Emadi, Ali
    • Journal of Electrical Engineering and Technology
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    • 제2권2호
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    • pp.231-240
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    • 2007
  • This paper presents an advanced modeling and simulation technique applied to DC/DC power electronic converters fed through renewable energy power sources. The distributed generation (DG) system at the Illinois Institute of Technology, which employs a phase-l system consisting of a photovoltaic-based power system and a phase-2 system consisting of a fuel cell based primary power source, is studied. The modeling and simulation of the DG system is done using the generalized state space averaging (GSSA) method. Furthermore, the paper compares the results achieved upon simulation of the specific GSSA models with those of popular computer aided design software simulations performed on the same system. Finally, the GSSA and CAD software simulation results are accompanied with test results achieved via experimentation on both, the PV-based phase-l system and the fuel cell based phase-2 power system.

A PROCEDURE FOR GENERATING IN-CABINET RESPONSE SPECTRA BASED ON STATE-SPACE MODEL IDENTIFICATION BY IMPACT TESTING

  • Cho, Sung-Gook;Cui, Jintao;Kim, Doo-Kie
    • Nuclear Engineering and Technology
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    • 제43권6호
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    • pp.573-582
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    • 2011
  • The in-cabinet response spectrum is used to define the input motion in the seismic qualification of instruments and devices mounted inside an electrical cabinet. This paper presents a procedure for generating the in-cabinet response spectrum for electrical equipment based on in-situ testing by an impact hammer. The proposed procedure includes an algorithm to build the relationship between the impact forces and the measured acceleration responses of cabinet structures by estimating the state-space model. This model is used to predict seismic responses to the equivalent earthquake forces. Three types of structural model are analyzed for numerical verification of the proposed method. A comparison of predicted and simulated response spectra shows good convergence, demonstrating the potential of the proposed method to predict the response spectra for real cabinet structures using vibration tests. The presented procedure eliminates the uncertainty associated with constructing an analytical model of the electrical cabinet, which has complex mass distribution and stiffness.

User Density Estimation System at Closed Space using High Frequency and Smart device

  • Chung, Myoungbeom
    • 한국컴퓨터정보학회논문지
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    • 제22권11호
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    • pp.49-55
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    • 2017
  • Recently, for safety of people, there are proposed so many technologies which detect density of people at the specific place or space. The representative technology for crowd density estimation was using image analysis method from CCTV images. However, this method had a weakness which could not be used and which's accuracy was lower at the dark or smog space. Therefore, in this paper, to solve this problem, we proposed a user density estimation system at closed space using high frequency and smart device. The system send inaudible high frequencies to smart devices and it count the smart devices which detect the high frequencies on the space. We tested real-time user density with the proposed system and ten smart devices to evaluate performance. According to the testing results, we confirmed that the proposed system's accuracy was 95% and it was very useful. Thus, because the proposed system could estimate about user density at specific space exactly, it could be useful technology for safety of people and measurement of space use state at indoor space.

Battery State Estimation Algorithm for High-Capacity Lithium Secondary Battery for EVs Considering Temperature Change Characteristics

  • Park, Jinho;Lee, Byoungkuk;Jung, Do-Yang;Kim, Dong-Hee
    • Journal of Electrical Engineering and Technology
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    • 제13권5호
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    • pp.1927-1934
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    • 2018
  • In this paper, we studied the state of charge (SOC) estimation algorithm of a high-capacity lithium secondary battery for electric vehicles (EVs) considering temperature characteristics. Nonlinear characteristics of high-capacity lithium secondary batteries are represented by differential equations in the mathematical form and expressed by the state space equation through battery modeling to extract the characteristic parameters of the lithium secondary battery. Charging and discharging equipment were used to perform characteristic tests for the extraction of parameters of lithium secondary batteries at various temperatures. An extended Kalman filter (EKF) algorithm, a state observer, was used to estimate the state of the battery. The battery capacity and internal resistance of the high-capacity lithium secondary battery were investigated through battery modeling. The proposed modeling was applied to the battery pack for EVs to estimate the state of the battery. We confirmed the feasibility of the proposed study by comparing the estimated SOC values and the SOC values from the experiment. The proposed method using the EKF is expected to be highly applicable in estimating the state of the high-capacity rechargeable lithium battery pack for electric vehicles.