• 제목/요약/키워드: derivative models

검색결과 132건 처리시간 0.024초

Robustness of optimized FPID controller against uncertainty and disturbance by fractional nonlinear model for research nuclear reactor

  • Zare, Nafiseh;Jahanfarnia, Gholamreza;Khorshidi, Abdollah;Soltani, Jamshid
    • Nuclear Engineering and Technology
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    • 제52권9호
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    • pp.2017-2024
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    • 2020
  • In this study, a fractional order proportional integral derivative (FOPID) controller is designed to create the reference power trajectory and to conquer the uncertainties and external disturbances. A fractional nonlinear model was utilized to describe the nuclear reactor dynamic behaviour considering thermal-hydraulic effects. The controller parameters were tuned using optimization method in Matlab/Simulink. The FOPID controller was simulated using Matlab/Simulink and the controller performance was evaluated for Hard variation of the reference power and compared with that of integer order a proportional integral derivative (IOPID) controller by two models of fractional neutron point kinetic (FNPK) and classical neutron point kinetic (CNPK). Also, the FOPID controller robustness was appraised against the external disturbance and uncertainties. Simulation results showed that the FOPID controller has the faster response of the control attempt signal and the smaller tracking error with respect to the IOPID in tracking the reference power trajectory. In addition, the results demonstrated the ability of FOPID controller in disturbance rejection and exhibited the good robustness of controller against uncertainty.

Analgesic Effect of DA-5018, a New Capsaicin Derivative, against Experimental Acute Pain (새로운 캅사이신 유도체 DA-5018의 급성통증 모델에서의 진통작용)

  • 손문호;배은주;김희기;신명수;김순희;김원배;양중의;박노상
    • Biomolecules & Therapeutics
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    • 제5권1호
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    • pp.67-73
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    • 1997
  • Analgesic effect of DA-5018, a new capsaicin derivative, was evaluated in various rat models of experimentally induced acute pain. DA-5018(0.2∼10.0 mg/kg, p.o.) prevented the writhing syndromes induced by acetic acid or phenol-p-benzoquinone(PBQ). It increased the pain threshold of inflamed paw when tested by the Randall-Selitto method at the dose of 2.0∼20.0 mg/kg by oral administration. And also it showed antinociceptive activities in tail-pinch(1.0∼20.0 mg/kg, p.o.) and tail-flick test(5.0∼50.0 mg/kg, p.o.). the potency and efficacy of DA-5018 were comparable to morphine · HCI in all the models mentioned above. Acetaminophen exhibited the inhibition of acetic acid-induced writhing syndromes and also analgesic activity in Randall-Selitto test, but it showed the limited efficacy in tail-pinch and tail-flick test. These results mean that DA-5018 has a broader analgesic activity profile than acetaminophen. And we found out that the analgesic activity of DA-5018 was 100 times more potent when administered centrally than administered orally in tail-flick test. These results suggest that DA-5018 has an orally active analgesic activity, and central nervous system may be involved in the action of DA-5018.

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Comparison of Performance of Models to Predict Hardness of Tomato using Spectroscopic Data of Reflectance and Transmittance (토마토 반사광과 투과광 스펙트럼 분석에 의한 경도 예측 성능 비교)

  • Kim, Young-Tae;Suh, Sang-Ryong
    • Journal of Biosystems Engineering
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    • 제33권1호
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    • pp.63-68
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    • 2008
  • This study was carried out to find a useful method to predict hardness of tomato using optical spectrum data. Optical spectrum of reflectance and transmittance data were collected processed by 9 kind of preprocessing methods-normalizations of mean, maximum and range, SNV (standard normal variate), MSC (multiplicative scatter correction), the first derivative and second derivative of Savitzky-Golay and Norris-Gap. With the preprocessed and non-processed original spectrum data, prediction models of hardness of tomato were developed using analytical tools of PLS (partial least squares) and MLR (multiple linear regression) and tested for their validation. The test of validation resulted that the analytical tools of PLS and MLR output similar performances while the transmittance spectra showed much better result than the reflectance spectra.

A SIMPLE VARIANCE ESTIMATOR IN NONPARAMETRIC REGRESSION MODELS WITH MULTIVARIATE PREDICTORS

  • Lee Young-Kyung;Kim Tae-Yoon;Park Byeong-U.
    • Journal of the Korean Statistical Society
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    • 제35권1호
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    • pp.105-114
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    • 2006
  • In this paper we propose a simple and computationally attractive difference-based variance estimator in nonparametric regression models with multivariate predictors. We show that the estimator achieves $n^{-1/2}$ rate of convergence for regression functions with only a first derivative when d, the dimension of the predictor, is less than or equal to 4. When d > 4, the rate turns out to be $n^{-4/(d+4)}$ under the first derivative condition for the regression functions. A numerical study suggests that the proposed estimator has a good finite sample performance.

Fractional order optimal control for biological model

  • Mohamed Amine Khadimallah;Shabbir Ahmad;Muzamal Hussain;Abdelouahed Tounsi
    • Computers and Concrete
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    • 제34권1호
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    • pp.63-77
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    • 2024
  • In this research, we considered fractional order optimal control models for cancer, HIV treatment and glucose.These models are based on fractional order differential equations that describe the dynamics underlying the disease.It is formulated in term of left and right Caputo fractional derivative. Pontryagin's Maximum Principle is used as a necessary condition to find the optimal curve for the respective controls over fixed time period. The formulated problems are numerically solved using forward backward sweep method with generalized Euler scheme.

Generating Complicated Models for Time Series Using Genetic Programming

  • Yoshihara, Ikuo;Yasunaga, Moritoshi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.146.4-146
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    • 2001
  • Various methods have been proposed for the time series prediction. Most of the conventional methods only optimize parameters of mathematical models, but to construct an appropriate functional form of the model is more difficult in the first place. We employ the Genetic Programming (GP) to construct the functional form of prediction models. Our method is distinguished because the model parameters are optimized by using Back-Propagation (BP)-like method and the prediction model includes discontinuous functions, such as if and max, as node functions for describing complicated phenomena. The above-mentioned functions are non-differentiable, but the BP method requires derivative. To solve this problem, we develop ...

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Fault Detection in Automatic Identification System Data for Vessel Location Tracking

  • Da Bin Jeong;Hyun-Taek Choi;Nak Yong Ko
    • Journal of Positioning, Navigation, and Timing
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    • 제12권3호
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    • pp.257-269
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    • 2023
  • This paper presents a method for detecting faults in data obtained from the Automatic Identification System (AIS) of surface vessels. The data include latitude, longitude, Speed Over Ground (SOG), and Course Over Ground (COG). We derive two methods that utilize two models: a constant state model and a derivative augmented model. The constant state model incorporates noise variables to account for state changes, while the derivative augmented model employs explicit variables such as first or second derivatives, to model dynamic changes in state. Generally, the derivative augmented model detects faults more promptly than the constant state model, although it is vulnerable to potentially overlooking faults. The effectiveness of this method is validated using AIS data collected at a harbor. The results demonstrate that the proposed approach can automatically detect faults in AIS data, thus offering partial assistance for enhancing navigation safety.

Predicting the Soluble Solids of Apples by Near Infrared Spectroscopy (I) - Multiple Linear Regression Models - (근적외선을 이용한 사과의 당도예측 (I) - 다중회귀모델 -)

  • ;W. R. Hruschka;J. A. Abbott;;B. S. Park
    • Journal of Biosystems Engineering
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    • 제23권6호
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    • pp.561-570
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    • 1998
  • The MLR(Multiple Linear Regression) models to estimate soluble solids content non-destructively were presented to make a selection of optimal photosensor utilized to measure the soluble solids content of apples. Visible and NIR absorbance in the 400 to 2498 nanometer(nm) wavelength region, soluble solids content(sugar content), hardness, and weight were measured for 400 apples(gala). Spectrophotometer with fiber optic probe was utilized for spectrum measurement and digital refractometer was used for soluble solids content. Correlation between absorbance spectrum and soluble solids content was analyzed to pick out the optimal wavelengths and to develop corresponding prediction model by means of MLR. For the coefficient of determination($R^2$) to be over 0.92, the MLR models out of the original absorbance were built based on 7 wavelengths of 992, 904, 1096, 1032, 880, 824, 1048nm, and the ones of the second derivative absorbance based on 5 wavelengths of 784, 1056, 992, 808, 872nm. The best model of the second derivative absorbance spectrum had $R^2$=0.91, bias= -0.02bx, SEP=0.28bx for unknown samples.

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Identification of fractional-derivative-model parameters of viscoelastic materials using an optimization technique (최적화 기법을 이용한 점탄성물질의 유리미분모델 물성값 추정)

  • Kim, Sun-Yong;Lee, Doo-Ho
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 한국소음진동공학회 2006년도 춘계학술대회논문집
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    • pp.1235-1242
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    • 2006
  • Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the nonlinear dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature with fewer parameters than conventional spring-dashpot models. However the identification procedure of the four-parameter is very time-consuming one. An efficient identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured FRFs coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment. A numerical example shows that the proposed method is efficient and robust in identifying the viscoelastic material parameters of fractional derivative model.

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