• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.944-948
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• 2004

This paper presents a simple torque estimation method and switching angle control of Switched Reluctance Motor (SRM) using Neural Network (NN). SRM has gaining much interest as industrial applications due to the simple structure and high efficiency. Adaptive switching angle control is essential for the optimal driving of SRM because of the driving characteristic varies with the load and speed. The proper switching angle which can increase the efficiency was investigated in this paper. NN was adapted to regulate the switching angle and nonlinear inductance modelling. Experimental result shows the validity of the switching angle controller.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.143-148
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• 2023

Among the characteristics of SRM, due to nonlinearity, it is difficult to properly operate to form maximum torque and minimum torque pulsation. In addition, in the case of fixed switching angle control, torque formation according to speed variation is unstable, thereby reducing efficiency. Therefore, active switching angle control according to speed variation is required. Therefore, active switching angle control according to speed variation is required. In this paper, a method for improving driving performance by reducing torque ripple by automatic control of the advance angle and increasing output torque was sought from the problem caused by the nonlinearity of the SRM. In addition, the optimal operation of SRM due to the switching variable according to the performance of the hysteretic current controller was examined.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.211-218
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• 1998

As a part of trajectory modulation to increase system survivability and terminal effectiveness, impact angle control is required in the terminal phase of tactical missile systems. The missile systems are not allowed to have high altitude to reduce probability of detection by sensors of missile defense systems. In this paper, an analytic form of a time-optimal control law is suggested in the case of constrained missile maneuverability and impact angle under the assumption of a zero-lag autopilot. The control law is obtained by establishing optimal missile-target engagement geometry in the vertical plane. Extension of the law for missiles with autopilot response lags requiring a numerical solution is studied by introducing an iterative algorithm for optimal switching time determination of which the initial switching instants are obtained from the analytic solution. Also suggested is a closed-form impact angle control law derived by an energy-optimal approach. The performances of the proposed guidance laws are evaluated by a series of computer runs.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.33-37
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• 2002

This paper presents a simple torque estimation method and the switching angle control of SRM using Neural Network. SRM has gaining much interest as industrial applications due to the simple structure and high efficiency. Adaptive switching angle control is essential for the optimal driving of a SRM because of the driving characteristic varies with the load and speed. The proper switching angle which can increase the efficiency was investigated in this paper Neural Network was adapted to regulate the switching angle and nonlinear inductance modelling. Experimental result shows the validity of the switching angle controller.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.4
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• pp.156-163
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• 2001

In this paper an optimal switching angle control of a switched reluctance motor (SRM) drive system is investigated for achieving maximum energy conversion ratio. A new magnetizing method is proposed with a low switching frequency. The proposed algorithm maximizes the positive energy conversion region, which is directly related to the mechanical output, and reduces the reactive power region with the same field energy region. As a consequence, a torque ripple is also sufficiently reduced compared with that of the conventional switching angle magnetizing method. Experimental results show that the proposed scheme provides a high efficiency and a low ripple drive.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.3
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• pp.252-258
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• 2010

If the speed measurement of resolver and the generation of PWM signals are implemented with single microcontroller, it is easy to reduce the system cost and to avoid the switching noise of inverters. To avoid the switching noise and to improve the accuracy of measurement, PWM switching and A/D sampling of the resolver should be synchronized. Phase angle of the resolver excitation signal is increased in stepwise manner, then, the output signal of the resolver is measured in each step. From the measured data, the optimal phase angle of resolver excitation signal is estimated using the least square approximation method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.518-521
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• 2004

We have investigated about compensation film to reduce the light leakage at an oblique angle in-plane switching mode. It is well known that uncompensated in-plane switching (US) and fringe field switching (FFS) liquid crystal displays (LCDs) have much better viewing angle than other modes owing to the in-plane rotation of the LC director. However, to accomplish optimal viewing angle characteristics in these devices, they must be compensated by one or more films. So, in this paper, we have studied how to reduce the light leakage with viewing angle using discotic film in dark state.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.4
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• pp.165-173
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• 2002

The goal of this paper is optimal switching angle of switched reluctance motor drive system fur maximum energy ratio. A new magnetizing method with a low-frequency increasing the energy conversion ratio that is related to the efficiency of motor is proposed. As the results, it improved the efficiency about 2[%]. And a torque ripple is also sufficiently reduced compared with that of the conventional approach. In order tn start softly regardless of large ripple torque, the profile of phase current is predicted by the ANFIS, and current control mode was adapted when it is operated under the starting speed. Variable implementations en the fields will guarantee the more practical drive system.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.6
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• pp.509-516
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• 2002

This paper presents a simple torque estimation method and switching angle control of Switched Reluctance Motor(SRM) using Neural Network(NN). SRM has gaining much interest as industrial applications due to the simple structure and high efficiency. Adaptive switching angle control is essential for the optimal driving of SRM because of the driving characteristic varies with the load and speed. The proper switching angle which can increase the efficiency was investigated in this paper. NN was adapted to regulate the switching angle and nonlinear inductance modelling. Experimental result shows the validity of the switching angle controller.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.239-243
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• 2004

This paper presents a proper switching angle calculation method of Switched Reluctance Motor (SRM) for drill. The characteristic of SRM drive is very related to the scheduling of commutation angle and current waveforms. Therefore, a selection method of switching turn-on and turn-off angle is suggested for adaptational operation of SRM with varied rotor speed and load. Simulation and experimental results are presented for the validation of proposed method.