• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7A
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• pp.620-627
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• 2005

We develop an adaptive hot-spot operating scheme(AHOS) to mitigate the negative effects from the nonuniform distribution of user location and the variation in the mixture of QoS requirements in OFDMA downlink systems. The base station in a macrocell can control the operation of picocells within the cell, and turns on or off according to the changes in the estimated user outage probability and the AHOS gain parameter. With the computer simulation, the AHOS has been proved to maximize the system throughput while maintaining the QoS outage probability very low under various system scenarios.

• ETRI Journal
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• v.28 no.3
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• pp.282-290
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• 2006

In vertically overlaid cellular systems, a temporary traffic concentration can occur in a hot-spot area, and this adversely affects overall system capacity. In this paper, we develop an adaptive hot-spot operating scheme (AHOS) to mitigate the negative effects from the nonuniform distribution of user location and the variation in the mixture of QoS requirements in orthogonal frequency division multiple access downlink systems. Here, the base station in a macrocell can control the operation of picocells within the cell, and turns them on or off according to the system overload estimation function. In order to determine whether the set of picocells is turned on or off, we define an AHOS gain index that describes the number of subcarriers saved to the macrocell by turning a specific picocell on. For initiating the picocell OFF procedure, we utilize the changes in traffic concentration and co-channel interference to the neighboring cells. According to computer simulation, the AHOS has been proved to have maximize system throughput while maintaining a very low QoS outage probability under various system scenarios in both a single-cell and multi-cell environments.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.225-227
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed artificial intelligent-PI(AIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.41-45
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• 2014

In this paper, a high-efficiency power amplifier is implemented by using a drain bias control circuit operated at low input power for WPT(Wireless Power Transfer). Adaptive bias control circuit was added to high-efficiency class-E amplifier. It was possible to obtain the overall improvement in efficiency by adjusting the drain bias at low input power. The proposed adaptive class-E amplifier is implemented by using the input and output matching network and serial resonant circuit for improvement in efficiency. Drain bias control circuit consists of a directional coupler, power detector, and operational amplifier for adjusting the drain bias according to the input power. The measured results show that output powers of 41.83 dBm were obtained at 13.56 MHz. At this frequency, we have obtained the power added efficiency(PAE) of 85.67 %. It was confirmed increase of PAE of an average of 8 % than the fixed bias from the low input power level of 0 dBm ~ 6 dBm.

• Journal of IKEEE
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• v.20 no.3
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• pp.299-302
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• 2016

In this paper, we designed the stack monitoring system with improved performance. To block the incoming pulse noise to the amplifier, shield and the power supply impedance are reduced and the power circuit is isolated. The control unit is developed with variable high voltage, adaptive gain, offset and threshold in order to match the scintillation detector characteristic to the apparatus. 300-1500V variable high voltage power circuit is configured applicable to various scintillation detector. Stack monitoring system with improved performance guarantee the efficiency and the reliability by considering the characteristic of various scintillation detector. Developed stack monitoring system is evaluated with certified testing equipment and shows excellent performance with respect to the uncertainty of the sensor test results.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.49-57
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• 1994

An efficient approach for the computationtion of the optimum convergence factor is proposed for the LMS algorithm applied to a transversal FIR structure in this study. The approach automatically leads to an optimum step size algorithm at each weight in every iteration that results in a dramatic reduction in terms of convergence time. The algorithm is evaluated in system identification application where two alternative computer simulations are considered for time-invariant and time-varying system cases. The results show that the proposed algorithm needs not appropriate convergence factor and has better performance than AGC(Automatic Gain Control) algorithm and Karni algorithm, which require the convergence factors controlled arbitrarily in computer simulation for time-invariant system and time-varying systems. Also, itis shown that the proposed algorithm has the excellent adaptability campared with NLMS(Normalized LMS) algorithm and RLS (Recursive least Square) algorithm for time-varying circumstances.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.458-460
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• 1996

In this study, the full-state flux observer is designed in the synchronous DQ-frame and the speed adaptation rule is derived by using the MRAS(Model Reference Adaptive System) theory. In this rule, the induction motor becomes a reference model and the flux observer is taken as a adjustable model. A guideline of the adaptation gain is investigated for the precise and stable speed adaptation and the proposed scheme is compared with the conventional one designed in the stationary DQ-frame.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1165-1168
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• 2001

The effect of sensor faults in DTC based induction motor drives is analyzed and a fault detection problem is treated. An adaptive gain scheduling observer is proposed for the design of DTC controller and a fault detection system. The observer provides not only the estimate of stator flux, a key variable in DTC system, but also the estimates of stator current, rotor speed that are useful for fault detection purpose. Simulations for various type of sensor faults are performed to evaluate the performance of the overall control system and the proposed sensor fault detection scheme.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.441-444
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• 1992

In this paper, for tracking and filtering seaway information which act as a control disturbance the adaptive notch filter which removes disturbance with fast convergence and stability without changing the value of gain parameter $\mu$ when statistical property of input signal varies rapidly is designed by improving conventional RMXMS(Recursive Maximum Mean Square) algorithm. Besides, in consideration of measurement noise of sensors in underwater vehicle, the system which removes the noise and the disturbance is suggested.