• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.4
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• pp.239-246
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• 2003

Application of the filtered-x Least Mean Square(LMS) adaptive filter to active noise control requires to estimate the transfer characteristics between the output and the error signal of the adaptive controller. In this paper, we derive the filtered-x adaptive noise control algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.9
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• pp.569-575
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.658-663
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• 1987

The new controller developed here, which is the facility with only one measurement, is a new concept for the level controller of the existing nuclear steam generator. A MACS (Microcomputer-based Adaptive Control System of a Steam Generator) is quite practical and efficient, and has also simple structure and higher flexibility in the installment for actual plant. A key ingredient of this system is adaptive regulator which can calculate adaptive, optimal valve position in response to changes in the dynamics of the process and the disturbances. In spite of many difficulties in the steam generator water level control at low power, it can be concluded from the experimental and simulation results, that the MACS can provide optimal, robust steam generator level control from zero to full power. The amount of the control input effort can be reduced by adjusting the weighting factor. However, the steady state water level errors are generated. To avoid the steady errors, the different adaptive algorithm should be investigated in the future. The 3 second sampling time is acceptable for this system. However, action should be taken to shorten the sampling time for better digital control.

• Journal of Power Electronics
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• v.9 no.2
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• pp.188-197
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• 2009

This paper presents an adaptive flux observer to estimate stator flux linkage and stator inductances of an interior permanent-magnet synchronous machine considering magnetic saturation. The concept of static and dynamic inductances due to saturation is introduced in the machine model to describe the relationship between current and flux linkage and the relationship between their time derivatives. A flux observer designed in the stationary reference frame with constant inductance is analyzed in the rotor reference frame by a frequency-response characteristic. An adaptive algorithm for an on-line inductance estimation is proposed and a Lyapunov-based analysis is given to discuss its stability. The dynamic inductances are estimated by using Taylor approximation based on the static inductances estimated by the adaptive method. The simulation and experimental results show the feasibility and performance of the proposed technique.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.3
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• pp.311-319
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• 1992

In this paper, a direct adaptive pole placement controller for an unknown linear time-invariant single-input single-output nonminimum phase plant is proposed. To design this direct adaptive pole placement controller, the auxiliary signals are introduced. Consequently, a linear equation error model is formulated for estimating both the controller parameters and the additional auxiliary parameters. To estimate the controller parameters and the additional auxiliary parameters, the exponentially weighted least-squares algorithm is implemented, and a method of selecting the characteristic polynomials of the sensitivity function filters is proposed. In this method, all the past measurement data are weighted exponentially. A series of simulations for a nonminimum phase plant is presented to illustrate some features of both the parameter estimation and the output response of this adaptive pole placement controller.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.112-125
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• 1999

In a robust regression model, it is typically assumed that the errors are normally distributed. However, what if the error distribution is deviated from the normality and the response variables are not completely observable due to censoring? For complete data, Kim and Lai(1998) suggested a new adaptive M-estimator with an asymptotically efficient score function. The adaptive M-estimator is based on using B-splines to estimate the score function and simple cross validation to determine the knots of the B-splines, which are a modified version of Kun( 1992). We herein extend this method to right-censored data and study how well the adaptive M-estimator performs for various error distributions and censoring rates. Some impressive simulation results are shown.

• Smart Structures and Systems
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• v.15 no.3
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.34-42
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• 1992

This paper presents two fast least-squares lattice algorithms for adaptive nonlinear filters equipped with bilinear system models. The lattice filters perform a Gram-Schmidt orthogonalization of the input data and have very good numerical properties. Furthermore, the computational complexity of the algorithms is an order of magnitude snaller than previously algorithm is an order of magnitude smaller than previously available methods. The first of the two approaches is an equation error algorithm that uses the measured desired response signal directly to comprte the adaptive filter outputs. This method is conceptually very simple`however, it will result in biased system models in the presence of measurement noise. The second approach is an approximate least-squares output error solution. In this case, the past samples of the output of the adaptive system itself are used to produce the filter output at the current time. Results of several experiments that demonstrate and compare the properties of the adaptive bilinear filters are also presented in this paper. These results indicate that the output error algorithm is less sensitive to output measurement noise than the squation error method.

• MALSORI
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• no.60
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• pp.181-190
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• 2006

This paper describes a speech enhancement scheme that leads to significant improvements in recognition performance when used in the ASR front-end. The proposed approach is based on adaptive comb filtering and an MMSE-related parameter estimator. While adaptive comb filtering reduces noise components remarkably, it is rarely effective in reducing non-stationary noises. Furthermore, due to the uniformly distributed frequency response of the comb-filter, it can cause serious distortion to clean speech signals. This paper proposes an improved comb-filter that adjusts its spectral magnitude to the original speech, based on the speech absence probability and the gain modification function. In addition, we introduce the modified comb filtering-based speech enhancement scheme for ASR in mobile environments. Evaluation experiments carried out using the Aurora 2 database demonstrate that the proposed method outperforms conventional adaptive comb filtering techniques in both clean and noisy environments.

• Animal cells and systems
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• v.5 no.1
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• pp.77-83
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• 2001

The present study was conducted to elucidate whether the expression level of poly(ADP-ribose) polymerase (PARP) is related to the ultraviolet radiation (UV)-induced apoptosis. After treatment of the mammalian cell lines HeLa S3 and Chinese hamster ovary (CHO) with 50 J/m2 UV, induction of apoptosis was determined by several means during 24 h post-incubation. Incidence of apoptosis was much lower in CHO than HeLa S3 cells based on the percentage of apoptotic cells in terms of morphological changes in nucleus or direct counting of viable cells and qualitative or quantitative DNA fragmentation. Interestingly, when the expression level of PARP was measured by western blotting, the amounts of PARP that was retained at each time point inversely correlated with the incidences of apoptosis in these cells. Concomitant with generation of the 85 kDa fragment, 116 kDa PARP disappeared in HeLa S3 within 6 h after UV treatment, whereas a fair amounts of 116 kDa band was still retained in CHO cells at 36 h post-incubation. This inverse relationship was also observed in the adaptive response system, in which cells weve treated with a high dose of UV after pretreatment with a low dose. As expected, typical adaptive responses appeared in CHO cells but not in HeLa cells, showing greater cell viability and lesser DNA fragmentation. During the adaptive response in CHO cells, PARP was expressed at much higher level compared to the single, high dose-treated cells. Interestingly, even though PARP was induced at 6 h post-incubation In both cell types, its expression was more prominent in CHO cells. Thus, our data indicate that the retained level of intact PARP against UV damage inversely correlates with incidence of apoptosis in mammalian cells, and also suggest that a machinery to protect the PARP degradation against UV damage exists in CHO but not in HeLa S3 cells.