• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.43-46
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• 1998

Many of the active noise control system utilize a form of the least mean square(LMS) algorithm. This paper discusses the dependence of the convergence rate on the acoustic error path in the popular algorithm which is conventional "filtered-x LMS" and introduces new algorithm "constrained filtered-x LMS". The proposed method increase the convergence region regardless of the time-delay in the acoustic error path. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the control process become stationary. Advantages of constrained filtered-x LMS algorithm is illustrated by convergence analysis in the mean sense.

• Journal of Astronomy and Space Sciences
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• v.29 no.4
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• pp.389-395
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• 2012

The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS). An ANFIS produces a control signal for one of the three axes of a spacecraft's body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw) and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.3
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• pp.223-230
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• 1999

A conventional sliding mode control approach is often impractical or difficult when it is applied to high order process b because the number of tuning parameters in the sliding mode controller increases with the order of the plant. C Camacho(l996) proposed a design method of a fixed structure sliding mode controller based on a first order plus dead t time approximation to the higher-order process. But, his method has such problems as chattering, over‘shoot, and c command following due to the Taylor the approximation en‘ors for the time delay term of the first order model. In this p paper, a new design technique for a sliding mode controller based on the modified Taylor approximation considered a w weight is developed to improve the Camacho's problems.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.174-182
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• 2002

System identification and controller formulation are essential in dynamic process control. In system identification, data for system identification are obtained, and then they are analyzed so that the system model of the process is built, identified, and diagnosed. In controller formulation, the control equation is derived based on the result of the system identification. There has been much theoretical research on system identification and controller formulation. These theories are very useful when they are appropriately applied. To our regret, however, these theories are not always effectively applied in practice because the engineers and the operators who manage the process often do not have the necessary understanding of required time series analysis methods. On the other hand, because of widespread use of statistical packages, system identification such as estimating ARMA models can be done with little understanding of time series analysis methods. Therefore, it might be said that the most theoretically difficult part in practice is the controller formulation. In this paper, lists of control equations are proposed as a useful tool for practitioners to use. The tool supports bridging the gap between theory and practice in dynamic process control. Also, for some models, the generalized control equations are obtained.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.3
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• pp.288-293
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• 2009

This study presents the active noise control of duct noise. The duct was excited by a steady-state harmonic and white noise force and the control was performed by one control speaker attached to surface of the duct. An adaptive controller based on filtered x LMS(FXLMS) algorithm was used and controller was defined by minimizing the square of the response of the error microphone. The assemble controller, which is called a hybrid ANC(active noise control) system, was combined with feedforward and feedback controller. The feedforward ANC attenuates primary noise that is correlated with the reference signal, while the feedback ANC cancels the narrowband components of the primary noise that are not observed by the reference sensor. Furthermore, in many ANC applications, the periodic components of noise are the most intense and the feedback ANC system has the effect of reducing the spectral peaks of the primary noise, thus easing the burden of the feedforward ANC filter.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.87-93
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• 2017

This paper investigates active noise control of tower-type air conditioners using the filtered-x least mean square (FXLMS) algorithm to reduce fan blower noise transmission. Firstly, the main components required for the active control system including the error sensor, the control speaker and the reference sensors are selected. Since the noise could significantly reduce if the reference signal includes every frequency response information, a various reference signals from accelerometers and a microphone are used. Secondly, the controller based on the FXLMS algorithm with a single-channel reference signal is implemented. Then, the control performance is examined experimentally for the different reference signals. It is found that the accelerometer signal well possesses the motor vibration related noise and a microphone signal could includes global noise. When using the reference signal with a microphone located near the motor and the fan blower, the active control system reduces the noise globally, except for several peaks.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.3
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• pp.215-223
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• 2016

In this study, a novel rotor position sensorless estimation method of an interior permanent-magnet synchronous motor is proposed. A square-wave pulsating voltage signal is injected in the estimated synchronous reference frame. This signal is interpreted in the stationary reference frame regardless of the estimated rotor position. Thus, assuming that the position error is nearly zero is unnecessary because the variables in the estimated synchronous reference frame are not used. The rotor position can be exactly calculated from two voltage references and three sampled current feedbacks in the stationary reference frame. The proposed method is easy to implement and helps enhance the bandwidth of the current controller. The validity of the proposed method is verified by simulations and experiments.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.1
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• pp.37-44
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• 1983

A class of adaptive control algorithms applied to discrete-time single-input single-output deterministic linear systems is analyzed by using direct model reference adaptive control. Controller parameters are identified with weighted least square Method. And computer simulations reveal that proposed weighted least square method in which the value of depends on the identification error can be used regardless of the sufficient condition of reference input signal.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.311-316
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• 2007

This paper proposes the algorithm which estimates moment of the inertia and friction coefficient of friction for high performance speed control of electric motor. The proposed algorithm finds the moment of inertia and friction coefficient of friction by observing the speed error signal generated by the speed observer and using Recursive Least-Mean-Square method(RLS). By feedbacking the estimated inertia and estimated coefficient of friction to speed controller and full order speed observer, then the errors of the inertia and coefficient of friction and speed due to the inaccurate initial value are decreased. Inertia and coefficient of friction converge to the actual value within several times of speed changing. Simulation and actual experiment results are given to demonstrate the effectiveness of the proposed parameter estimator.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.66-77
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• 1997

This paper presents an automatic tuning method for parameters of a multivaiable self-tuning velocity-type PID controller which adapts to changes in the system parameters with time delays and noises. The velocity-type PID control structure is determined in the process of minimizing the variance of the auxiliarly output, and self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optiminzing the design parameters of the controller. The proposed PID type multivariable self-tuning method is simple andeffective compared with other esisting multivariable self-tuning methods. Computer simulation has shown that the proposed algorithm is beter than the trial-and-error method in the tracking performance.