• Journal of the Korean Statistical Society
• /
• v.12 no.1
• /
• pp.46-56
• /
• 1983

An algorithm based on EM procedure which finds maximum likelihood estimators in a nonlinear regression with censored data is proposed, and asymptotic properties of the estimator are investigated in detail. Some numerical examples are also given.

• Communications for Statistical Applications and Methods
• /
• v.6 no.2
• /
• pp.345-356
• /
• 1999

This paper deals with the problem of estimating regression coefficients in nonlinear regression model having random regressor. The sufficient conditions for consistency of the $L_1$-estimator with random regressor are given and discussed in this paper. An example is given to illustrate the application of the main results.

• Journal of Advanced Marine Engineering and Technology
• /
• v.21 no.5
• /
• pp.571-578
• /
• 1997

This paper presents a method for designing a control system to stand upright inverted triangle. A linearized model is obtained form the nonlinear system by Taylor series expansion and a state controller is designed based on the model. After implementing the control system which is combined control law and estimator with reference input, experiments are carried out to stand upright inverted triangle at any angluar position.

• Journal of the Korean Statistical Society
• /
• v.30 no.1
• /
• pp.31-39
• /
• 2001

For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.18-20
• /
• 2006

The statistics for the neighbor differences between the particular pixels and their neighbors are introduced. They are incorporated into the filter to remove additive Gaussian noise contaminating images. The derived denoising method corresponds to the maximum likelihood estimator for the heavy-tailed Gaussian distribution. The error norm corresponding to our estimator from the robust statistics is equivalent to Huber's minimax norm. Our estimator is also optimal in the respect of maximizing the efficacy under the above noise environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.350-355
• /
• 1997

The problem of mathematical model for an unknown system by measureing its input-output data pairs is generally referred to as state estimates. The state estimation problem is often of importance in its own right since we may want to know the value of the states. For instance, in navigation, we may take noisy positional fixes using satelite or radar navigation, and the estimator can use these measurements to provide accurate estimates of current position, hedaing, and velocity. And the state estimates can also be used for control purposes. Then it is very important to know the state of plant. In this paper, the theory of the minimization of a loss function was used to design the fuzzy system. Here, the used teory is Least Square Esimation method. This parametrization has the Linear in the parameters charcteristic that allows standard parameter estimation technique to be used to estimate the parameters of the fuzzy system. The combination of the fuzzy system and the estimation m thod then performs as a nonlinear estimator. If several fuzzy label are defined for the input variables at the antecedent part, the fuzzy system then behaves as a collection of nonlinear estimators where different regions of rules have different parameters. In simulation results, the fuzzy model controlled a difference in the structure between the actual plant and the fuzzy estimator. It is also proved that the fuzzy system is equivalent to its transformed system. therefore we was able to get the state space equation of system with the estimated paramater.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.6
• /
• pp.93-99
• /
• 2007

Robust nonlinear image denoising algorithms for the class of ${\alpha}$-stable distribution are introduced. The proposed amplitude-limited sample average filter(ALSAF) proves to be the maximum likelihood estimator under the heavy-tailed Gaussian noise environments. The error norm for this estimator is equivalent to Huber#s minimax norm. It is optimal in the respect of maximizing the efficacy under the above noise environment. It is mired with the myriad filter to propose an amplitude-limited myriad filter(ALMF). The behavior and performance of the ALSAF and ALMF in ${\alpha}$-stable noise environment are illustrated and analyzed through simulation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.4
• /
• pp.254-260
• /
• 2000

This paper deals with the development of fault tolerant control for a nonlinear boiler system with noise and disturbance. The MCMBPC(Multivariable Constrained Model Based Predictive Control) is adopted for the control of the specific boiler turbin model. The fault detection and diagnosis are accomplished with the Kalman filter and two bias estimators. Once a fault is detected, two Bias estimators are driven to estimate the fault and to discriminate Process fault and sensor fault. In this paper, a fault tolerant control scheme combining MCMBPC with a fault compensation method based on the bias estimator is proposed. The proposed scheme has been applied to the nonlinear boiler system and shown a satisfactory performance through some simulations.

• Transactions of The Korea Fluid Power Systems Society
• /
• v.2 no.4
• /
• pp.7-13
• /
• 2005

This paper presents modeling and ostimator/controller design for the hydraulic system in Vehicle Stability Control(VSC) system. A nonlinear mathematical model of the VSC hydraulic system is proposed and its accuracy is experimentally verified. A brake pressure estimator is then designed based on the derived mathematical model of VSC hydraulic system. And a disturbance observer, which compensates the estimation error between the brake pressure and the computed brake pressure is also designed to enhance the accuracy of the estimator. The proposed controller has the form of a feedback controller and determines explicitly the on/off ratio of valves' driving PWM signals by means of making use of the simplified mathematical model in the VSC hydraulic system. The performance of the designed controller whose feedback signal is generated by the brake pressure estimator is validated through experimental results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.1
• /
• pp.1-7
• /
• 2009

As designing PID control on aircraft, we consider a gain scheduling on altitude and velocity. If pitot tube is not installed in the unpowered air vehicle, the control performance is reduced by the difference between ground speed and air speed with a wind considered. In this paper, a simple guidance controller (LOS: Line of Sight) and the wind estimator using Kalman filter are designed. And we minimize the wind effect through the estimator. Finally, we perform the 6-DOF nonlinear simulation with the wind model to verify the performance of the controller with the wind estimator.