• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.5-11
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• 1996

The purpose of this paper is to propose a method improving the performance of a semi-continuous hidden Markov model(SCHMM) speaker adaptation system which uses Bayesian Parameter reestimation approach. The performance of Bayesian speaker adaptation could be degraded in case that the features of a new speaker are severely different from those of a reference codebook. The excessive codewords of the reference codebook still remain after adaptation proess. which cause confusion in recognition process. To solve such problems, the proposed method uses formant information which is extracted from the cepstral coefficients of the reference codebook and adaptation data. The reference codebook is adapted to represent the formant distribution of a new speaker and it is used for Bayesian speaker adaptation as an initial codebook. The proposed method provides accurate correspondence between reference codebook and adaptation data. It was observed that the excessive codewords were not selected during recognition process. The experimental results showed that the proposed method improved the recognition performance.

• Journal of Power Electronics
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• v.14 no.1
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• pp.125-134
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• 2014

This paper presents a robust and speed-sensorless stator flux estimation for induction motor direct torque control. The proposed observer is based on sliding mode approach. Stator electrical equations are used in the rotor orientation reference frame to eliminate the observer dependence on rotor speed. Lyapunov's concept for systems stability is adopted to confine the observer gain. Furthermore, the sensitivity of the observer to parameter mismatch is recovered with an adaptation technique. The nonlinearities of the pulse width modulation voltage source inverter are estimated and compensated to enhance stability at low speeds. Therefore, a new method based on the model reference adaptive system is proposed. Simulation and experimental results are shown to verify the feasibility and effectiveness of the proposed algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.347-353
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• 2003

A nonlinear speed controller for a surface mounted permanent magnet synchronous motor (PMSM) based on a newly developed adaptive backstepping approach is presented To compensate parameter uncertainties and load torque disturbance, a nonlinear adaptive backstepping control law and adaptive law are derived systematically through virtual control input and suitable Lyapunov function. Also, speed observer without using costly speed sensor is presented. Simulation results show that the proposed controller can observe the speed and track the reference speed signal generated by a reference model.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.1-10
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• 2005

This paper proposes a new and simple input prediction method for robust servo system. A robust tracking control system for optical disk drives was proposed recently based on both Coprime Factorization (CF) and Zero Phase Error Tracking (ZPET) control. The CF control system can be designed simply and systematically. Moreover, this system has not only stability but also robustness to parameter uncertainties and disturbance rejection capability. Since optical disk tracking servo system can detect only tracking error, it was proposed that the reference input signal for ZPET could be estimated from tracking errors. In this paper, we propose a new control structure for the ZPET controller. It requires less memory than the previously proposed method for the reference signal generation. Numerical simulation results show that the proposed method is effective.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.124-132
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• 2004

A hydraulic system is difficult to keep the performance due to non-linearity, load pressure which changes according to working condition and system parameter variation, the requirement of control algorithm has been risen in order to satisfy them. An adaptive control is a control method which is suggested to achieve a control object though plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp, adaptive control can keep the characteristics of closed-loop system regularly. In this study GMVAC(generalized minimum variance adaptive control) combined with output error feedback is proposed in order to solve problems of non-minimum phase, vibration and overshoot in initial response of the plant. The control performance according to the variation of characteristics of the plant is evaluated by changing the supply pressure only.

• Journal of Power System Engineering
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• v.4 no.3
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• pp.62-71
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• 2000

A mathematical modeling for a magnetic levitation system is proposed using the Taylor series expansion of differential function for obtaining linearity. It is confirmed that this kind of linear approximation method can be used to the modeling of a magnetic levitation system. The two-degree-of-freedom optimal servo system for a constant reference signal is proposed using the LQ optimization technique. An additional state feedback is introduced at the output of the integrator to cancel the integral action for reference signal if there is no modeling error of the plant and no disturbance input to the plant. When the modeling error or the disturbance input exists, the integral effect appears. The system has a free parameter which can b used to tune the effect of the integral compensation.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.8-14
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• 2005

This paper is proposed hybrid artificial intelligent(HAI) controller for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on HAI 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 HAI 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.

• 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.

• Journal of Power Electronics
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• v.18 no.2
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• pp.492-501
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• 2018

In the rotor-flux oriented control used in induction motors, the electrical parameters of the motors should be identified. Among these parameters, the mutual inductance and rotor resistance should be accurately tuned for better operations. However, they are more difficult to identify than the stator resistance and stator transient inductance. The rotor resistance and mutual inductance can change in operations due to flux saturation and heat generation. When detuning of these parameters occurs, the performance of the control is degenerated. In this paper, a novel method for the concurrent identification of the two parameters is proposed based on recursive least square estimation and model reference adaptive control.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.346-349
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• 1994

This paper is concerned with a motion control of a manipulator under parametric uncertainties and external disturbances. The parametric uncertainties are regarded as internally generated disturbances in the manipulator. Based on this idea, we formulate a model reference control problem with desired disturbance attenuation. The solution of this control problem not only reduces the worst-case effect on tracking error due to internal and external disturbances (combined disturbances) as much as possible, but also achieve optimal tracking when perturbations are absent. In order to solve the control problem which is formulated in this paper we reduce it to a constrained minmax cost control problem. A differential game theory is used to treat this constrained minmax cost control problem. The differential game theory leads to a sufficient condition for the global solvability of the model reference control problem with desired disturbance attenuation.