• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.813-816
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• 1999

In this paper is Proposed a VSC(variable structure controller) for a high-speed and high-precision position control of a XY Table, which is based on the PI type reaching mode. Also the comparative study between the proposed method and the conventional PID controller is presented as well. Designed and tuned under repeated experiments, the proposed method showed a better reasonable performance than PID controller in the aspect of tracking error.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.146-154
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• 1988

The computer simulation of speed and phase control system has been carried out in this study. The load of permanent magnet type synchronous motor is not constant in this system. The cost function method has been used in obtaining the optimal gain of PI controller and the rotor position angle of phase controller has been compensated depending on the load and speed variation. This analysis also shows that the current of d-axis component is zero under the variable a load conditions and the torque per unit current can be maximized.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.282-284
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• 2006

Generally PI controller is used to control the speed of an induction motor. It has the good performance of speed control in case of adjusting the control parameters. But it occurred the problem to change the control parameters in the change of operation condition. In order to solve this problem, Fuzzy control or Artificial neural network is introduced in the speed control of an induction motor. However, Fuzzy control have the problems as the difficulties to change the membership function and fuzzy rule and the remaining error. Also Neural network has the problem as the difficulties to analyze the behavior of inner part. Therefore, the study on the combination of two controller is proceeded. In this paper, Speed controller of an induction motor based fuzzy-neural network is proposed and the speed control of an induction motor is performed using the proposed controller. Through the experiment, the fast response and good stability of the proposed speed controller is proved.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.9
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• pp.26-35
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• 2010

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. This controller is controlled speed and current using hybrid PI(HBPI) controller and estimation of speed using ANN. Also, this paper is proposed maximum torque control of induction motor using slip angular speed and current condition at widely speed range. The performance of the proposed induction motor drive with maximum torque control using HBPI controller is verified by analysis results at dynamic operation conditions.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.389-394
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• 2004

This paper proposes a speed estimation method using FLC(Fuzzy Logic Controller) in order to realize the speed control of PMAM(Permanent Magnet AC Motor) with no speed sensor. This method uses FLC as a adaptive laws of MRAS(Model Reference Adaptive System) and estimates the rotor speed of PMAM with a difference between the reference model and the adjustable model. Speed control is performed by PI controller with the estimated speed. The experiment is executed to verify the propriety and the effectiveness of the proposed system.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.1
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• pp.41-50
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• 1999

The brushless DC motor is widely being used in unmanned factories for its easy maintenance and characteristics of controllability. In this paper, we designed a speed control servo system of a sinusoidal type bmshless DC motor which has high efficiency and usefulness in the industrial fields. This servo system is realized by a controller which is required for driving motors and a new auto-tuning PI control algorithm. The DSP(Digita1 Signal Processor) is adopted as a main controller and a sensor signal processor owing to its fast computational capability and suitable architecture. Also, the hardware PWnl(Pulse Width Modulation) current controller is implemented to pursue a speed command exactly. By experimental results, it is verified that the speed response is pursued fast after command value and the steady-state response is well converged for command value variation without overshoots.

• Journal of Power Electronics
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• v.14 no.1
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• pp.74-81
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• 2014

In this study, a brain emotional learning-based intelligent controller (BELBIC) is developed for the speed control of an interior permanent magnet synchronous motor (IPMSM). A novel and simple model of the IPMSM drive structure is established with the intelligent control system, which controls motor speed accurately without the use of any conventional PI controllers and is independent of motor parameters. This study is conducted in both real time and simulation with a new control plant for a laboratory 3 ph, 3.8 Nm IPMSM digital signal processor (DSP)-based drive system. This DSP-based drive system is then compared with conventional BELBIC and an optimized conventional PI controller. Results show that the proposed method performs better than the other controllers and exhibits excellent control characteristics, such as fast response, simple implementation, and robustness with respect to disturbances and manufacturing imperfections.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.955-957
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• 1998

Switched reluctance motor(SRM) has the advantages of simple structure, low rotor inertia, and high poer rate per unit volume. However, position sensor isessential in SRM in order to synchronize the phase excitation to the rotor position. The position sensors increase the cost of drive system, and tend to reduce system reliability. This paper investigtes the speed control of sensorless SRM. The proposed system consists of position detection circuit, dwell angle controller, digital logic commutator, PI speed controller and 4-phase inverter. The performances in the proposed system are verified through the experiment.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.7
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• pp.1112-1120
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• 1994

This paper presents a servo control scheme for the surface-mounted permanent-magnet synchronous motor(SPMSM) which essentially uses vector control algorithm. The control system is composed of the PI controller for speed control and the current controller using space voltage vector PWM technique. The high-speed calculation and processing for vector control is carried out by TMS320C31 digital signal processor and IGBT module. The proposed scheme is verified through digital simulations and experiments for 2.2kW SPMSM and shows good dynamic performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.9
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• pp.33-43
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• 2011

Since the fuzzy neural network(FNN) is universal approximators, the development of FNN control systems have also grown rapidly to deal with non-linearities and uncertainties. However, the major drawback of the existing FNNs is that their processor is limited to static problems due to their feedforward network structure. This paper proposes the recurrent FNN(RFNN) for high performance and robust control of SynRM. RFNN is applied to speed controller for SynRM drive and model reference adaptive fuzzy controller(MFC) that combine adaptive fuzzy learning controller(AFLC) and fuzzy logic control(FLC), is applied to current controller. Also, this paper proposes speed estimation algorithm using artificial neural network(ANN). The proposed method is analyzed and compared to conventional PI and FNN controller in various operating condition such as parameter variation, steady and transient states etc.