• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.4-141
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• 2001

In this paper the Local Weighted Regression LWR technique is applied to the estimation of aircrcraft parameters. The method consists In improving the Local Weighted Regression LWR technique by adding a data Retention-and-Deletion RD strategy. The improvement comes with reduced computational effort since the two techniques can share their main computational procedures. The purpose of the study was to establish if the proposed algorithm could provide fast and reliable real-time estimations, with accuracy comparable to other well-known off-line identification schemes. The algorithm was tested using specific parameter estimation maneuvers and flight data of the NASA F/A-18 HARV. The results were compared with both the estimation obtained from ...

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.305-317
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• 2004

We construct the empirical Bayes (EB)estimation of the parameter in two-side truncated distribution families with asymmetric Linex loss using negatively associated (NA) samples. The asymptotical optimality and convergence rate of the EB estimation is obtained. We will show that the convergence rate can be arbitrarily close to $O(n^{-q}),\;q\;=\;{\lambda}s(\delta\;-\;2)/\delta(s\;+\;2)$.

• Journal of the Korean Statistical Society
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• v.32 no.3
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• pp.289-298
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• 2003

We consider the estimation problem for the scale parameter of the Rayleigh distribution using weighted balanced loss function (WBLF) which reflects both goodness of fit and precision. Under WBLF, we obtain the optimal estimator which creates a kind of balance between Bayesian and non-Bayesian estimation. We also deal with the estimation of R ＝ P(Y < X) when Y and X are two independent but not identically distributed Rayleigh distribution under squared error loss function.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.84-93
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• 2010

This paper describes a method of visualization and fast estimation of parameter in continuous time signal. The parameter estimation method of this paper directly estimate the parameters on the basis of the discrete Fourier transform. Also, this paper present to efficient visualization method of dominant parameters obtained in continuous time signal. The proposed methods are applied to test functions with three dominant modes. The results show that the proposed methods are highly applicable to parameter estimation and visualization in continuous time signal.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.916-924
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• 2008

In this paper dynamic modeling parameters were estimated using a frequency domain estimation method. A systematic flight test method was employed using preprogrammed multistep excitation of the swashplate control input. In addition when one axis is excited, the autopilot is engaged in the other axis, thereby obtaining high-quality flight data. A dynamic model was derived for a small scale unmanned helicopter (CNUHELI-020, developed by Chungnam National University) equipped with a Bell-Hiller stabilizer bar. Six degree of freedom equations of motion were derived using the total forces and moments acting on the small scale helicopter. The dynamics of the main rotor is simplified by the first order tip-path plane, and the aerodynamic effects of fuselage, tail rotor, engine, and horizontal/vertical stabilizer were considered. Trim analysis and linearized model were used as a basic model for the parameter estimation. Doublet and multistep inputs are used to excite dynamic motions of the helicopter. The system and input matrices were estimated in the frequency domain using the equation error method in order to match the data of flight test with those of the dynamic modeling. The dynamic modeling and the flight test show similar time responses, which validates the consequence of analytic modeling and the procedures of parameter estimation.

• Bulletin of the Korean Chemical Society
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• v.24 no.3
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• pp.279-284
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• 2003

The One Pass Method (OPM) previously presented for the identification of single input single output systems is used to estimate the parameters of a Decentralized Control System (DCS). The OPM is a linear and therefore a simple estimation method. All of the calculations are performed in one pass, and no initial parameter guess, iteration, or powerful search methods are required. These features are of interest especially when the parameters of multi input-output model are estimated. The benefits of the OPM are revealed by comparing its results against those of two recently published methods based on pulse testing. The comparison is performed using two databases from the literature. These databases include single and multi input-output process transfer functions and relevant disturbances. The closed loop responses of these processes are roughly captured by the previous methods, whereas the OPM gives much more accurate results. If the parameters of a DCS are estimated, the OPM yields the same results in multi or single structure implementation. This is a novel feature, which indicates that the OPM is a convenient and practice method for the parameter estimation of multivariable DCSs.

• Smart Structures and Systems
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• v.26 no.6
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• pp.735-751
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• 2020

Identification of structure parameters is crucial in Structural Health Monitoring (SHM) context for activities such as model validation, damage assessment and signal processing of structure response. In this paper, guided waves generated by piezoelectric transducers are used for in-situ and non-destructive structural parameter estimation based on Bayesian approach. As Bayesian approach needs iterative process, which is computationally expensive, this paper proposes a method in which an analytical model is selected and developed in order to decrease computational time and complexity of modeling. An experimental set-up is implemented to estimate three target elastic and geometrical parameters: Young's modulus, Poisson ratio and thickness of aluminum and steel plates. Experimental and simulated data are combined in a Bayesian framework for parameter identification. A significant accuracy is achieved regarding estimation of target parameters with maximum error of 8, 11 and 17 percent respectively. Moreover, the limitation of analytical model concerning boundary reflections is addressed and managed experimentally. Pulse excitation is selected as it can excite the structure in a wide frequency range contrary to conventional tone burst excitation. The results show that the proposed non-destructive method can be used in service for estimation of material and geometrical properties of structure in industrial applications.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1174-1179
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• 2008

Many modeling and calibration methods have been developed to analyze and design the biological wastewater treatment process. For the systematic use of activated sludge model (ASM) in a real treatment process, a most important step in this usage is a calibration which can find a key parameter set of ASM, which depends on the microorganism communities and the process conditions of the plants. In this paper, a standardized calibration protocol of the ASM model is developed. First, a weighted effluent quality index(WEQI) is suggested far a calibration protocol. Second, the most sensitive parameter set is determined by a sensitive analysis based on WEQI and then a parameter optimization method are used for a systematic calibration of key parameters. The proposed method is applied to a calibration problems of the single carbon removal process. The results of the sensitivity analysis and parameter estimation based on a WEQI shows a quite reasonable parameter set and precisely estimated parameters, which can improve the quality and the efficiency of the modeling and the prediction of ASM model. Moreover, it can be used for a calibration scheme of other biological processes, such as sequence batch reactor, anaerobic digestion process with a dedicated methodology.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.975-981
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• 2012

The SNR estimation performance of hierarchical 16QAM system, which is adopted to simultaneous transmission or efficient image transmission system, is analyzed. Hierarchical 16QAM is modulation system which has different constellation shape from conventional QAM and can provide users with high quality and low quality of data services simultaneously by controlling hierarchical modulation parameter. Assuming AWGN channel, SNR estimation performance characteristics are investigated considering hierarchical modulation parameter and type of constellation points. From simulation results, it is found that constellation point showing superior SNR estimation performance relative to other points is exist. Also, it is known that according to hierarchical modulation parameter, SNR estimation range with more accurate estimation performance is divided.