• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.109-119
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• 1999

Switched Reluctance Motor(SRM) have been expanding gradually their awlications in the variable speed drives due to their relatively low cost, simple and robust structure, controllability and high efficiency. In this paper neural network theory is used to detemrine fuzzy-neural network controller's membership ftmctions and fuzzy rules. In addition neural network emulator is used to emulate forward dynamics of SRM and to get error signal at fuzzy-neural controller output layer. Error signal is backpropagated through neural network emulator. The backpropagated error of emulator offers the path which reforms the fuzzy-neural network controller's mmbership ftmctions and fuzzy rules. 32bit Digital Signal Processor(TMS320C31) was used to achieve the high speed control and to realize the fuzzy-neural control algorithm. Simulation and experimental results show that in the case of load variation the proposed control rrethcd was superior to a conventional rrethod in the respect of speed response.sponse.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.4
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• pp.98-106
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• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the cower and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and f-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent(HAI) controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.5
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• pp.1-9
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• 2007

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the coner and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1211-1214
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• 1992

AC servo motor drives, Fara DS series, proposed in this paper can be effectively used in robots, CNC machine tools, and FA system with AC servo motors as actuators. The inverter of the AC servo drive consists of IGBT (Insulated Gate Bipolar Transistor) which have high switching frequency. Noises and vibrations generated in variable speed control of AC servo motors can be greatly reduced due to their high switching frequencies. In the developed servo drive, maximum torque is always generated in the whole speed range by compensating phase shift, which results from the nonlinearies of the AC servo motor during abrupt acceleration and deceleration. Abundant protection functions are provided to prevent abnormal state of the servo motor, and furthermore diverse user options are considered provided for the effective application. The proposed AC servo motor drive is designed to minimize velocity variation with respect to external load, supply voltage, environmental temperature, and humidity, so can be widely used in the fields of factory automation including robots and CNC msachine tools.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.743-744
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• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent(HAI) controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.425-431
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• 2011

The harmonic distortion level may be significant in electric propulsion systems, as the main loads usually are variable speed propulsion/thruster drives. Distortion of currents and supply voltage waveforms may lead to: Increased power dissipation(losses) in equipment connected to the network, such as generators, motors, transformers, cables, etc., from the harmonic currents, may cause overheating and deterioration of the insulation, and reduced life time of the equipment. In this paper introduced the canceling method of harmonic currents by a multipulse drive with phase shifting transformer. The simulation results indicated a good speed response to the middle speed range of electric propulsion motor. And also, THD(total harmonic distortion) and torque ripple could be reduced in comparing the 12-pulse drive with 6-pulse drive.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.29-31
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on fuzzy-neural networks (FN)-PI controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses In variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2618-2624
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• 2009

Harmonics (or distortion in wave form) has always existed in electrical power systems. It is harmless as long as its level is not substantial. However, with the recent rapid advancement of power electronics technology, so-called nonlinear loads, such as variable frequency drives for motor power/speed control, are increasingly finding their way to shipboard or offshore applications. In this paper a new approach to direct torque control (DTC) of induction motor drive is presented. In comparison with the conventional DTC methods the inverter switching frequency is constant and is dramatically increased, requiring neither any increase of the sampling frequency, nor any high frequency dither signal. The well-developed space vector modulation technique is applied to inverter control in the proposed DTC-based induction motor drive system, thereby dramatically reducing the current harmonics. As compared to the existing DTC approach with constant inverter switching frequency, the presented new approach does not invoke any concept of deadbeat control, thereby dramatically reducing the computations.

• Journal of Power Electronics
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• v.15 no.3
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• pp.753-762
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• 2015

This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC method.