• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2538-2541
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• 2005

This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.394-405
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• 2020

The parameters of transmission lines have an influence on the electromagnetic environment surrounding the line. This paper proposes a method based on phasor measurement unit (PMU) and supervisory control and data acquisition (SCADA) to achieve online estimation of transmission line full parameters, such as resistance, reactance and susceptance. The proposed full parameter estimation method is compared with the traditional method of estimating resistance independently based on SCADA system. Then, the electromagnetic environment is analyzed based on the different parameter estimation methods. The example results illustrate that online estimation of transmission line full parameters is more accurate in the analysis of electromagnetic environment, which further confirms its necessity and significance in engineering application.

• 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.

• Water for future
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• v.27 no.1
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• pp.89-99
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• 1994

Flood forecasting in Korea has been based on the off-line parameter estimation method. But recent flood forecasting studies explore on-line recursive parameter estimation algorithms. In this study, a simultaneous adaptive estimation of system states and parameters for rainfall-runoff model is investigated for on-line real-time flood forecasting and parameter estimation. The proposed flood routing system is composed of Flood forecasting in Korea has been based on the off-line parameter estimation method. But recent flood forecasting studies explore on-line recursive parameter estimation algorithms. In this study, a simultaneous adaptive estimation of system states and parameters for rainfall-runoff model is investigated for on-line real-time flood forecasting and parameter estimation. The proposed flood routing system is composed of ø-index in the assessment of effective rainfall and the cascade of nonlinear reservoirs accounting for translation effect in flood routing. To combine the flood routing model with a parameter estimation model, system states and parameters are treated with the extended state-space formulation. Generalized least squares and maximum a posterior estimation algorithms are comparatively examined as estimation techniques for the state-space model. The sensitivity analysis is to investigate the identifiability of the parameters. The index of sensitivity used in this study is the covariance matrix of the estimated parameters.-index in the assessment of effective rainfall and the cascade of nonlinear reservoirs accounting for translation effect in flood routing. To combine the flood routing model with a parameter estimation model, system states and parameters are treated with the extended state-space formulation. Generalized least squares and maximum a posterior estimation algorithms are comparatively examined as estimation techniques for the state-space model. The sensitivity analysis is to investigate the identifiability of the parameters. The index of sensitivity used in this study is the covariance matrix of the estimated parameters.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.1
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• pp.36-41
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• 2016

The development need of new renewable energy is more and more important to resolve exhaustion of chemical fuels and environmental pollution. Polymer electrolyte membrane fuel cell has been widely studied to the extent that it can be used commercially. But there are many problems to be solved. One of them is to enhance the stability of fuel cell stacks. This paper proposes a new fault diagnosis method using Least Square Method (LSM) which is one of parameter estimation methods. The proposed method extracts equivalent circuit parameters from on-line measurements. Parameters of the circuit are estimated according to normal and abnormal states using simulation. The variation of parameters estimated in each states enables the estimation of state in fuel cells. Thus the LSM presented can be a suitable on-line parameter estimation method in PEMFC.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.4
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• pp.206-210
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• 2004

This paper deals with a parameter estimation of the DC-DC converter system for its diagnosis. Especially, we present the results of parameter estimation for the DC-DC converter model by the system identification method. The parameter estimation for the DC-DC converter system aims at the diagnosis of its operating status. For the operating status diagnosis of the DC-DC converter system, we assume that the DC-DC converter system is an equivalent model of the Buck converter and estimate the main parameter for on-line diagnosis. In addition, for verification of an estimated parameter, we compare a bode plot of the estimated system transfer function and measurement results of the HP4194 instrument. It is a control system analyzer for system transfer function measurement. Our results confirm that the main parameter for diagnosis of the DC-DC converter system can be estimated by the system identification method and that the aging status of the system can be predicted by these results on operating status.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.481-486
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• 2002

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-5) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control. Based on the derived design method, the parameter estimation for controllable canonical T-S fuzzy model is also Presented.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.327-337
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• 2002

This paper applies a recently developed on-line parameter identification (PID) technique to sets of real flight data and compares the results with those of a state-of-the-art off-line PID technique. The on-line PID technique takes Linear Regression from Fourier Transformed equations and the off-line PID is based on the traditional Maximum Likelihood method. Sets of flight data from the NASA F/A-18 High Alpha research Vehicle (HARV) circraft, which has been recorded from specifically designed maneuvers and used for our line parameter estimation, are used for this study. The emphasis is given on the accuracy and on-line measure of reliability of the estimates. The comparison is performed for both longitudinal and lateral-directional dynamics for maneuvers at angles of attack ranging u=20°through $\alpha$=40°. Results of the two estimation processes are also compared with baseline wind tunnel estimates whenever possible.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.193-195
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• 2003

This paper presents an approach to estimate the power transmission line parameter by phasor measurement units(PMUs), which are synchronized to 1 pps signal of GPS. Existing approaches to estimate power transmission line parameter, are mainly off-line ones, based on faults or switching events on other neighboring lines. In this paper, to obtain static and dynamic properties of power transmission line parameter in service, the prototype of pmu-based Transmission Line Parameter Monitoring System (TLPMS) is proposed. Also, an technique to estimate parameters of transmission line described as 2-port network model and the soundness of estimated parameters are addressed.

• Journal of Mechanical Science and Technology
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• v.20 no.8
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• pp.1224-1231
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• 2006

The stability and control derivatives of DURUMI-lI UAV using the flight test are obtained. The flight test data is gathered from the normal flight condition (normal mode) and the flight condition assumed as the right elevator fixed (fault mode). Using real-time parameter estimation techniques, applied to Fourier transform regression method, simulates the aircraft motion. From the result, the fault of control surface is to be detected. In this paper, the results of the real- time parameter estimation techniques are compared with the results of the Advanced Aircraft Analysis (AAA). Using the aerodynamic derivatives, it provides the base line of normal/failure for the control surface by using the on-line parameter estimation of Fourier transform regression. In flight, this approach maybe helpful to detect and isolate the fault of primary control surface. It is explained how to perform the flight condition assumed as the right elevator fixed in the flight test. Also, it is mentioned how to switch between the normal flight condition and the assumed fault flight condition.