• KSBB Journal
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• v.10 no.5
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• pp.533-539
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• 1995

An autolytic system based on a thermally inducible phage lambda, λHL1, has been applied for the recovery of poly(3-hydroxybutyrate) [PHB] from a recombinant Escherichia coli XL1-Blue, harbouring a plasmid (pSYL105) containing the Alcaligenes eutrophus PHB biosynthesis genes. The lytic capability ofλHL1 was evaluated in flask culture for both lysogens, XL1-Blue (λHL1) and XL1-Blue (λHL1, pSYL105). When the optical density of culture at 600nm(OD600) reached 0.2, cell lysis was induced by increasing the temperature from $30^{\circ}C$ to $42^{\circ}C$. Most cells of XL1-Blue ($\lambda$HL1) were lysed by the autolytic system in an hour after the thermal induction, while the lytic efficiency was slightly lower for XLl-Blue (λHL1, pSYL105). The existence of pSYL105 in cells seemed to inhibit, to some extent, the lytic capability of λHL1 even at low PHB content. The lylic efficiency remarkably decreased as the induction was delayed to allow PHB accumulation. When a chemical induction using 2% (v/v) chloroform was introduced after an hours of thermal induction, we could obtain a good lytic efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2378-2381
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• 2003

In recent years, fuzzy logic has received greater emphasis in the field of power electronics and motion control by virtue of its adaptive capability. A new fuzzy logic based soft-start scheme for induction motor drives close to load detection has been discussed here using microcontroller based thyristorised voltage controller. Rule based soft-start algorithm is fully realised through a software approach only. The soft-start strategy is based on the change of input impedance during starting period. The prototype has been tested under various loading conditions and found to be reliable.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.4
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• pp.375-379
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• 2013

In this paper, the magnetic coupling between an induction cooker and a metallic pot is studied for various winding topologies. Effects of the winding orientation on the power transfer capability and on the emitted magnetic field under the cooker are discussed and compared. A novel topology inspired by permanent magnet Halbach array is proposed. This consists in coupling in both horizontal and vertical directions and to create an asymmetric field in order to reduce the emission under the cooker.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.179-181
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• 2004

This paper is proposed an adaptive fuzzy-neural network(A-FNN) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using A closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.225-232
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• 1994

In this paper, a new approach for the induction machine control whih ensures producing maximum torque per ampere over the entire field weakening region is presented. In addition, the relation of the output torque capability with the leakage factor of the machine is examined. Also the smooth and precise transition into the field weakening operation can be achieved by adjusting the base speed for the field weakening operation according to the flux level, the current limit and the voltage limit. The proposed is verified through simulation and experiment for a 5hp laboratory induction motor drive system.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.177-180
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed estimation and control of speed of induction motor using ANN Controller. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of Power Electronics
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• v.6 no.1
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• pp.67-72
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• 2006

This paper introduces two different types of AC current control methods for an indirect vector controlled induction motor using a matrix converter. The proposed methods combine the advantages of matrix converters with the advantages of the indirect vector AC current control methods. The first proposed method explains the basic idea of the hysteresis current control method for matrix converters and shows its capability and stability in comparison to the conventional method usually used for VSI. With the aid of the special configuration of the matrix converter, we also propose another current method which is modified from the first one in order to reduce both current ripple and torque ripple. Simulation results have verified the feasibility and the effectiveness of the proposed methods.

• Journal of Power Electronics
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• v.10 no.2
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• pp.194-202
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• 2010

The main cause of degradation in an unbalanced stand-alone doubly-fed induction generator (DFIG) system is negative sequence components that exist in the generated stator voltages. To eliminate these components, a hybrid current controller composed of a proportional-integral controller and a resonant regulator is developed in this paper. The proposed controller is applied to the rotor-side converter of a DFIG system for the purpose of compensating the negative stator voltage sequences. The proposed current controller is implemented in a single positive rotating reference frame and therefore the controller can directly regulate both the positive and negative sequence components without the need for sequential decomposition of the measured rotor currents. In terms of compensation capability and accuracy, simulations and experimental results demonstrated the excellent performance of the proposed control method when compared to conventional vector control schemes.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.463-471
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• 1999

This paper presents a vector controlled induction motor is implemented by neural networks system compared with PI controller for the speed control. The design employed the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE) for speed. In order to update the weights of the controller First of all Emulator updates its parameters by identifying the motor input and output next it supplies the error path to the output stage of the controller using backpropagation algorithm, As Controller produces an adequate output to the system due to neural networks learning capability Vector controlled induction motor characteristics actual motor speed with based on neural network system follows the reference speed better than that of linear PI speed controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.307-312
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• 2007

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of induction motor using FLC-FNN and estimation of speed using ANN controller The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.