• Title/Summary/Keyword: discrete time model

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Dynamic ice force estimation on a conical structure by discrete element method

  • Jang, HaKun;Kim, MooHyun
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.13 no.1
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    • pp.136-146
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    • 2021
  • This paper aims to numerically estimate the dynamic ice load on a conical structure. The Discrete Element Method (DEM) is employed to model the level ice as the assembly of numerous spherical particles. To mimic the realistic fracture mechanism of ice, the parallel bonding method is introduced. Cases with four different ice drifting velocities are considered in time domain. For validation, the statistics of time-varying ice forces and their frequencies obtained by numerical simulations are extensively compared against the physical model-test results. Ice properties are directly adopted from the targeted experimental test set up. The additional parameters for DEM simulations are systematically determined by a numerical three-point bending test. The findings reveal that the numerical simulation estimates the dynamic ice force in a reasonably acceptable range and its results agree well with experimental data.

Robust Nonlinear H$\infty$ FIR Filtering for Time-Varying Systems

  • Ryu, Hee-Seob;Son, Won-Kee;Kwon, Oh-Kyu
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.3
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    • pp.175-181
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    • 2000
  • This paper investigates the robust nonlinear H$_{\infty}$ filter with FIR(Finite Impulse Response) structure for nonlinear discrete time-varying uncertain systems represented by the state-space model having parameter uncertainty. Firstly, when there is no parameter uncertainty in the system, the discrete-time nominal nonlinear H$_{\infty}$ FIR filter is derived by using the equivalence relationship between the FIR filter and the recursive filter, which corresponds to the standard nonlinear H$_{\infty}$ filter. Secondly, when the system has the parameter uncertainty, the robust nonlinear H$_{\infty}$ FIR filter is proposed for the discrete-time nonlinear uncertain systems.

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Identification of flutter derivatives of bridge decks using CFD-based discrete-time aerodynamic models

  • Zhu, Zhiwen;Gu, Ming
    • Wind and Structures
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    • v.18 no.3
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    • pp.215-233
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    • 2014
  • This paper presents a method to extract flutter derivatives of bridge decks based on a combination of the computational fluid dynamics (CFD), system simulations and system identifications. The incompressible solver adopts an Arbitrary Lagrangian-Eulerian (ALE) formulation with the finite volume discretization in space. The imposed sectional motion in heaving or pitching relies on exponential time series as input, with aerodynamic forces time histories acting on the section evaluated as output. System identifications are carried out to fit coefficients of the inputs and outputs of ARMA models, as to establish discrete-time aerodynamic models. System simulations of the established models are then performed as to obtain the lift and moment exerting on the sections to a sinusoidal displacement. It follows that flutter derivatives are identified. The present approaches are applied to a hexagon thin plate and a real bridge deck. The results are compared to the Theodorsen closed-form solution and those from wind tunnel tests. Satisfactory agreements are observed.

Stable discrete-time adaptive control for periodic systems

  • Ishitobi, Mitsuaki;Iwai, Zental
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10a
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    • pp.717-720
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    • 1987
  • This paper presents a discrete-time model reference adaptive control technique for periodically time-varying plants. It is shown that the identification problem for periodic parameters can be reduced to that of constant unknown parameters case. The global stability of the resulting closed-loop system is established using the key technical lemma of Goodwin, Ramadge and Caines.

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Chaotic Synchronization of Using HVPM Model (HVPM 모델을 이용한 카오스 동기화)

  • 여지환;이익수
    • Journal of Korea Society of Industrial Information Systems
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    • v.6 no.4
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    • pp.75-80
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    • 2001
  • In this paper, we propose a new chaotic synchronization algorithm of using HVPM(Hyperchaotic Volume Preserving Maps) model. The proposed chaotic equation, that is, HVPM model which consists of three dimensional discrete-time simultaneous difference equations and shows uniquely random chaotic attractor using nonlinear maps and modulus function. Pecora and Carrol have recently shown that it is possible to synchronize a chaotic system by sending a signal from the drive chaotic system to the response subsystem. We proposed coupled synchronization algorithm in order to accomplish discrete time hyperchaotic HVPM signals. In the numerical results, two hyperchaotic signals are coupled and driven for accomplishing to the chaotic synchronization systems. And it is demonstrated that HVPM signals have shown the chaotic behavior and chaotic coupled synchronization.

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POSTERIOR COMPUTATION OF SURVIVAL MODEL WITH DISCRETE APPROXIMATION

  • Lee, Jae-Yong;Kwon, Yong-Chan
    • Journal of the Korean Statistical Society
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    • v.36 no.2
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    • pp.321-333
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    • 2007
  • In the proportional hazard model with the beta process prior, the posterior computation with the discrete approximation is considered. The time period of interest is partitioned by small intervals. On each partitioning interval, the likelihood is approximated by that of a binomial experiment and the beta process prior is by a beta distribution. Consequently, the posterior is approximated by that of many independent binomial model with beta priors. The analysis of the leukemia remission data is given as an example. It is illustrated that the length of the partitioning interval affects the posterior and one needs to be careful in choosing it.

GENERATING SAMPLE PATHS AND THEIR CONVERGENCE OF THE GEOMETRIC FRACTIONAL BROWNIAN MOTION

  • Choe, Hi Jun;Chu, Jeong Ho;Kim, Jongeun
    • Bulletin of the Korean Mathematical Society
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    • v.55 no.4
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    • pp.1241-1261
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    • 2018
  • We derive discrete time model of the geometric fractional Brownian motion. It provides numerical pricing scheme of financial derivatives when the market is driven by geometric fractional Brownian motion. With the convergence analysis, we guarantee the convergence of Monte Carlo simulations. The strong convergence rate of our scheme has order H which is Hurst parameter. To obtain our model we need to convert Wick product term of stochastic differential equation into Wick free discrete equation through Malliavin calculus but ours does not include Malliavin derivative term. Finally, we include several numerical experiments for the option pricing.

A New Consideration for Discrete-System Reduction via Impulse Response Gramian

  • Younseok Choo;Park, Jaeho
    • International Journal of Control, Automation, and Systems
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    • v.2 no.3
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    • pp.384-389
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    • 2004
  • Recently a method of model reduction for discrete systems has been proposed in the literature based on a new impulse response Gramian. In this method, the system matrix$A_r$ of a reduced model is computed by approximating the reduced-order impulse response Gramian. The remaining matrices $b_r$ and $c_r$ are obtained so that various initial Markov parameters and time-moments of the original system are preserved in the reduced model. In this paper a different approach is presented based on the recursive relationship among the impulse response Gramians.

A New Combined Approximation for the Reduction of Discrete-Time Systems Using Routh Stability Array and MSE (이감직신간 제어계에 있어서 Routh안정기열과 MSE 을 이용한 새로운 혼합형 모델 절기법)

  • 권오신;김성중
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.8
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    • pp.584-593
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    • 1987
  • A new combined approximation method using Routh stability array and mean-square error (MSE) method is proposed for deriving reduced-order z-transter functions for discrete time systems. The Routh stability array is used to obtain the reduced-order denominator polynomial, and the numerator polynomial is obtained by minimizing the mean-square error between the unit step responses of the original system and reduced model. The advantages of the new combined approximation method are that the reduced model is always stable provided the original model is stable and the initial and steady-state characteristics of the original model can be preserved in the reduced model.

Online Fuzzy Modelling of Nonlinear Systems Using a Genetic Algorithm (유전알고리즘을 이용한 비선형 시스템의 온라인 퍼지 모델링)

  • 이현식;오정환;신위재;김종화;진강규
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.3
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    • pp.80-87
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    • 1998
  • This paper presents and online scheme for fuzzy modelling of nonlinear systems, based on the model adjustment technique and the genetic algorithm technique. The fuzzy model is characterized by fuzzy "if-then" rules which represent locally linear input-output relations whose consequence parts are defined as subsystems of a nonlinear sysem. The discrete-time model for each subsystem is obtained to deal with initalization and unmeasurable signal problems in online estimation and the final output of the fuzzy model is computed from the outputs of the discrete-time models. Then, the parameters of both the premise and consequence parts of the fuzzy model are adjusted by a genetic algorithm. A set of simulation works is carried out to demonstrate the effectiveness of the proposed method.ed method.

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