• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.659-667
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• 2013

If the regression model or the propensity model is correct, the unbiasedness of the estimator using doubly robust imputation can be guaranteed. Using a neural network instead of a logistic regression model for the propensity model, the estimators using doubly robust imputation are approximately unbiased even though both assumed models fail. We also propose a doubly robust estimator of ratio form using population information of an auxiliary variable. We prove some properties of proposed theory by restricted simulations.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.387-395
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• 2007

We propose a doubly robustified estimating function for the estimation of parameters in the context of ARCH models. We investigate asymptotic properties of estimators obtained as solutions of robust estimating equations. A simulation study shows that robust estimator from specified doubly robustified estimating equation provides better performance than conventional robust estimators especially under heavy-tailed distributions of innovation errors.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.487-495
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• 2015

This paper proposes a new robust decentralized power oscillation dampers (POD) design of doubly-fed induction generator (DFIG) wind turbine for damping of low frequency electromechanical oscillations in an interconnected power system. The POD structure is based on the practical $2^{nd}$-order lead/lag compensator with single input. Without exact mathematical model, the inverse output multiplicative perturbation is applied to represent system uncertainties such as system parameters variation, various loading conditions etc. The parameters optimization of decentralized PODs is carried out so that the stabilizing performance and robust stability margin against system uncertainties are guaranteed. The improved firefly algorithm is applied to tune the optimal POD parameters automatically. Simulation study in two-area four-machine interconnected system shows that the proposed robust POD is much superior to the conventional POD in terms of stabilizing effect and robustness.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.47-55
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• 2011

Ratio and regression imputations depend on the model of a survey variable and the relation between the survey variable and auxiliary variables. If the model is not true, the unbiasedness of the estimator using the ratio or regression imputation cannot be guaranteed. In this paper, we develop the doubly robust imputation, which satisfies the approximate unbiasedness of the estimator, whether the model assumption is valid or not. The proposed imputation increases the efficiency of estimation by using the population information of the auxiliary variables. The simulation study establishes the theoretical results of this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.56-61
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• 2012

This paper propose the robust stability algorithm for controlling a variable speed wind power system which based on doubly-fed induction generator (DFIG). The control object in the wind power system enables the rotor to rotate without any physical contact by using magnetic force. Generally, the system dynamics of the wind power system has severe nonlinearity and uncertainty so that it is not easy to obtain the control objective. For solving these problems, we propose the fuzzy modelling and robust control algorithm for wind power system. The sufficient conditions for robust controller are obtained in terms of solutions to linear matrix inequalities (LMIs). Simulation results for wind power system based on DFIG are demonstrated to visualize the feasibility of the proposed method.

• Journal of Power Electronics
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• v.11 no.5
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• pp.719-725
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• 2011

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine lumped uncertainty. The overall system stability is proved by the Lyapunov theorem. It is shown that the torque and flux tracking errors as well as the updated weights of the ANN are uniformly ultimately bounded. Finally, effectiveness of the proposed control approach is shown by computer simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.269-277
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• 2012

When there are mismatches between the beamforming steering vector and the array response vector for the desired signal, the performance can be severely degraded as the adaptive array attempts to suppress the desired signal as well as interferences. In this paper, an robust method is proposed for the adaptive array in the presence of both direction errors and random errors in the steering vector. The proposed method first finds a signal-plus-interference subspace (SIS) from the correlation matrix, which in turn is exploited to extract an interference subspace based on the structure of a uniform linear array (ULA), the effect of the desired signal direction vector being reduced as much as possible. Then, the weight vector is attained to be orthogonal to the interference subspace. Simulation shows that the proposed method, in terms of signal-to-interference plus noise ratio (SINR), outperforms existing ones such as the doubly constrained robust Capon beamformer (DCRCB).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.115-122
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• 2011

Adaptive arrays suffer from severe performance degradation when there are errors in the steering vector. The DCRCB (doubly constrained robust Capon beamformer) overcomes such a problem, introducing a spherical uncertainty set of the steering vector together with a norm constraint. However, in the standard DCRCB, it is a difficult task to determine the bound for the uncertainty, the radius of the spherical set, such that a near best solution is obtained. A novel beamforming method is presented which has no difficulty of the uncertainty bound setting, employing a recursive search for the steering vector. Though the basic idea of recursive search has been known, the conventional recursive method needs to set a parameter for the termination of the search. The proposed method terminates it by using distances to the signal subspace, without the need for parameter setting. Simulation demonstrates that the proposed method has better performance than the conventional recursive method and than the non-recursive standard DCRCB, even the one with the optimum uncertainty bound.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.2
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• pp.152-162
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• 2008

This paper presents a sliding mode controller (SMC) to directly control the active and reactive powers of a doubly ffd induction generator (DFIG) for wind turbines. Sliding-mode control (SMC) and space-vector modulation (SVM) are combined to ensure high-performance operation. SMC scheme is designed to provide robust and fast power controls without frame transformation and current controller used in the conventional FOC drive. Simulation results and experimental results demonstrate that proposed methods preserve the effectiveness and robustness during variations of active and reactive power.

• Journal of Power Electronics
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• v.8 no.1
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• pp.10-22
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• 2008

The wind-driven doubly fed induction generator (DFIG) is currently under pressure to be more grid-compatible. The main concern is the fault ride-through (FRT) requirement to keep the generator connected to the grid during faults. In response to this, the paper introduces a novel model and new control scheme for the DFIG. The model provides a means of direct stator power control and considers the stator transients. On the basis of the derived model, a robust linear quadratic (LQ) controller is synthesized. The control law has proportional and integral actions and takes account of one sample delay in the input owing to the microprocessor's execution time. Further, the influence of the grid voltage imperfection is mitigated using frequency shaped cost functional method. Compensation of the rotor current pulsations is proposed to improve the FRT capability as well as the generator performance under grid voltage unbalance. As a consequence, the control system can achieve i) fast direct power control without instability risk, ii) alleviation of the problems associated with the DFIG operation under unbalanced grid voltage, and iii) high probability of successful grid FRT. The effectiveness of the proposed solution is confirmed through simulation studies on 2MW DFIG.