• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.1017-1028
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• 2009

NSRPM (Neyman-Scott Rectangular Pulse Model) is one of the common model for generating future precipitation time series in stochastical hydrology. There are 5 parameters to compose the NSRPM model for generating precipitation time series. Generally parameter estimation using moment has some problems related with increased objective functions and shows different results in accordance with random variable generating models. In this study, direct parameter estimation method was proposed to cover with disadvantages of parameter estimation using moment. To apply the direct parameter estimation, generating stochastical data variance in accordance with numbers of precipitation events of NSRPM was done. Both kinds of methods were applied at the Cheongju gauge station data. Precipitation time series were generated using 4 different random variable generator, and compared with observed time series to check the accuracies. As a results, direct method showed more stable and better results.

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.135-144
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• 2011

Direct parameter estimation method is verified with various models based on Neyman-Scott rectangular pulse model (NSRPM). Also, newly modified NSRPM (NMSRPM) that uses normal distribution is developed. Precipitation data observed by Korea Meteorological Administration (KMA) for 47 years is applied for parameter estimation. For model performance verification, we used statistics, wet ratio and precipitation accumulate distribution of precipitation generated. The comparison of statistics indicates that absolute relative error (ARE)s of the results from NSRPM and modified NSRPM (MNSRPM) are increasing on July, August, and September and ARE of NMNSRPM shows 10.11% that is the smallest ARE among the three models. NMNSRPM simulates the characteristics of precipitation statistics well. By comparing the wet ratio, MNSRPM shows the smallest ARE that is 16.35% and by using the graphical analysis, we found that these three models underestimate the wet ratio. The three models show about 2% of ARE of precipitation accumulate probability. Those results show that the three models simulate precipitation accumulate probability well. As the results, it is found that the parameters of NSRPM, MNSRPM and NMNSRPM are able to be estimated by the direct parameter estimation method. From the results listed above, we concluded that the direct parameter estimation is able to be applied to various models based on NSRPM. NMNSRPM shows good performance compared with developed model-NSRPM and MNSRPM and the models based on NSRPM can be developed by the direct parameter estimation method.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.5
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• pp.413-419
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• 2004

In the induction motor direct vector control system using the Gopinath model flux observer, the deterioration of the dynamic response due to the detuned rotor time constant is investigated. To solve this problem, the on line estimation algorithm of the rotor time constant using model reference adaptive control is proposed. The effect of the motor parameter variation on the rotor time constant estimation is analyzed through experiment. The estimation error due to the parameter variation converges within 5%. Thus applying the proposed algorithm to the Gopinath model flux observer, the robust direct vector control system of the induction motor to the parameter variation can be implemented.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.76-81
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• 1998

This paper presents an on-line scheme for parameter estimation of continuous-time systems, based on the model adjustment technique and the genetic algorithm technique. To deal with the initialisation and unmeasurable signal problems in on-line parameter estimation of continuous-time systems, a discrete-time model is obtained for the linear differential equation model and approximations of unmeasurable states with the observable output and its time-delayed values are obtained for the nonlinear state space model. Noisy observations may affect these approximation processes and degrade the estimation performance. A digital prefilter is therefore incorporated to avoid direct approximations of system derivatives from possible noisy observations. The parameters of both the model and the designed filter are adjusted on-line by a genetic algorithm, A set of simulation works for linear and nonlinear systems is carried out to demonstrate the effectiveness of the proposed method.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1211-1222
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• 2017

In order to decrease the parameter sensitivity of deadbeat direct torque control (DB-DTC), an improved deadbeat direct torque control method for surface mounted permanent-magnet synchronous motor (SPMSM) drives is proposed. First, the track errors of the stator flux and torque that are caused by model parameter mismatch are analyzed. Then a sliding mode observer is designed, which is able to predict the d-q axis currents of the next control period for one-step delay compensation, and to simultaneously estimate the model parameter disturbance. The estimated disturbance of this observer is used to estimate the stator resistance offline. Then the estimated resistance is required to update the designed sliding-mode observer, which can be used to estimate the inductance and permanent-magnetic flux linkage online. In addition, the flux and torque estimation of the next control period, which is unaffected by the model parameter disturbance, is achieved by using predictive d-q axis currents and estimated parameters. Hence, a low parameter sensitivity DB-DTC method is developed. Simulation and experimental results show the validity of the proposed direct control method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.337-340
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• 1997

In this paper we propose direct and indirect adaptive controllers for a nonlinear multivariable steam generating unit(200MW). In the direct adaptive scheme the estimation of the controller parameter are achieved from tracking error, while in the indirect approach the unknown parameter of the boiler system is estimated by the Hopfield network-based identifier. The performance of two proposed adaptive controllers is shown through simulations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.9
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• pp.1480-1490
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• 1997

A method by which the system parameter matrices can be estimated from measured time data of excitation force and acceleration has been studied. The acceleration data are integrated numerically to obtain the velocities and displacements, and the systm parameters are estimated from these data by solving equations of motion. The characteristics of the method have been investigated through its application to simulated data of 1 DOF and 2 DOF systems and experimental data measured from a simple structure. It was found that the method is very sensitive to measurement noise and the accuracy of the estimated parameters can be improved by averaging the repeatedly measured data and removing the noise. One of the main advantages of the parameter estimation method is that no a priori information about the system under test is required. The method can be easily extended to non-linear parameter estimation.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2246-2248
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• 2001

This paper presents a new vector control scheme for induction motor. An exact knowledge of the rotor flux position is essential for a high-performance vector control. The position of the rotor flux is measured in the direct schemes and estimated in the indirect schemes. Since the estimation of the flux position requires a priori knowledge of the induction motor parameters, the indirect schemes are machine parameter dependent. The rotor and stator resistance among the parameters change with temperature. Variations in the parameters of induction machine cause deterioration of both the steady state and dynamic operation of the induction motor drive. Several methods have presented to minimize the consequences of parameter sensitivity in indirect scheme. In this paper, new estimation scheme of rotor flux position is presented to eliminate sensitivity due to variation in the resistance. The simulation is executed to verify the proposed vector control performance and to compare its performance with that of indirect and direct vector control.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.113-118
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• 2003

The proposed rotor time constant estimation method can be applied to the direct vector control system of induction motor with flux observer In this paper the flux observer proposed by Gopinath model are used. This paper presents a new scheme for on-line estimation of rotor time constant using estimated rotor flux phase and current model rotor flux phase. The major advantage of this method are its dynamic correction capability, simplicity and accuracy as well as independence from change in motor parameter. simulation results are presented which demonstrate the effectiveness of the on line rotor time constant estimation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.80.2-80
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• 2002

The problem of sound source localization is to determine the position of sound sources using the measurement of the acoustic signals received by microphones. To develop a good sound source localization system which is applicable to a mobile platform such as robots, a time delay estimator with low computational complexity and robustness to background noise or reverberations is necessary. In this paper, an explicit adaptive time delay estimation method for a sound source localization system is proposed. Proposed explicit adaptive time estimation algorithm employs direct adaptation of the delay parameter using a transform-based optimization technique, rather than...