• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.154-157
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• 2006

This paper is proposed hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design..of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1523-1534
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• 2017

A Current Error Space Phasor (CESP) based hysteresis controller with online computation of the boundary for two-level inverter fed Induction Motor (IM) drives is presented in this paper. The stator voltages estimated along the ${\alpha}$-and ${\beta}$-axes and the orthogonal current error components of the motor are used in the online computation of the hysteresis boundary. All of the inherent benefits of space phasor based hysteresis controllers such as its quick dynamic response and nearby voltage vector switching are present in the proposed scheme with the added benefit of suppressing switching frequency variations. The similarity in the frequency spectrum of the phase voltage obtained at the output of the inverter using the proposed scheme and Bus Clamping Pulse Width Modulation (BCPWM) based drive is justified with the help of extensive MATLAB SIMULINK simulations. The controller is experimentally verified with a three phase, 2.2 kW IM drive for steady state and transient conditions and the obtained results match the simulation results.

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.48-58
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• 2011

In this paper, an attempt has been made to design the current and speed proportional and integral (PI) regulators of self-commutating current source inverter-fed induction motor drive having capacitors at the machine end and to investigate the transient performance of the same for step changes in reference speed. The mathematical model of the complete drive system is developed in closed loop, and the characteristic equations of the systems are derived using perturbation about steady-state operating point in order to develop the characteristic equations. The D-partition technique is used for finding the stable region in the parametric plane. Frequency scanning technique is used to confirm the stability region. Final selection of the regulator parameters is done by comparing the transient response of the current and speed loops for step variations in reference. The performance of the drive is observed analytically through MATLAB simulation.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.761-768
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• 2017

This paper deals with the performance analysis of three phase induction motor considering its stator side faults and operating thermal limits. The speed control of induction motor using three phase boost converter operated by a MOSFET switch and a PI controller is demonstrated and presented in this article. IGBTs switches are used for inverter drive mechanism. The experimental result of speed control of induction motor using voltage control technique clearly shows better accuracy than conventional methods of speed control. A three phase 1HP 415V 0.78 kW 4 Pole induction motor is designed using motor solver software. Based on the parameters used in the software thermal analysis of induction motor is done and torque variation with conductor area, efficiency, output curve, losses in different parts of motor has been obtained. Also different types of faults namely under voltage, over voltage, stator imbalanced voltage, turn to turn, locked rotor bar, wrong alignment of rotor bar with respect to stator are studied and fault analysis is performed. Hence comparison is made based upon the results obtained before and after faults.

• 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.

• Journal of Power Electronics
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• v.13 no.4
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• pp.656-668
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• 2013

This paper presents a wavelet-fuzzy based controller for indirect field oriented control of three-phase induction motor drives. The discrete wavelet transform is used to decompose the error between the actual speed and the command speed of the induction motor drive into different frequency components. The transformed error coefficients along with the scaling gains are used for generating the control component of the motor. Self-tuning fuzzy logic is used for online tuning of the scaling gains of the controller. The proposed controller has the ability to meet the speed tracking requirements in the closed loop system. The complete indirect field oriented control scheme incorporating the proposed wavelet-fuzzy based controller is investigated theoretically and simulated under various dynamic operating conditions. The simulation results are compared with a conventional proportional integral controller and a fuzzy based controller. The speed control scheme incorporating the proposed controller is implemented in real time using a digital processor control board. Simulation and experimental results validate the effectiveness of the proposed controller.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1376-1382
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• 2010

The propulsion Motor system has changed from the DC motor system to the induction motor system. Although the induction motor system has almost reached the stage of maturity, this system also need changed to the IPMSM system for direct drive without reduction gear. Thus, the IPMSM(Interior buried Permanent magnet synchronous Motor) has been adopted to meet the driving specification. In this paper, loss characteristic analysis of IPMSM has been performed using adopted F.E.M.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.829-833
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• 2001

In a conventional speed sensorless stator flux­oriented (SFO) induction machine drive system, the estimated speed is delayed in transients by the use of a low pass filter. This paper investigates the problem of a conventional speed sensorless SFO system due to the delay of the estimated speed in the field weakening region. In addition, this paper proposes a method to estimate exactly speed by using Kalman filter. The proposed method is verified by simulation and experiment with a 5-hp induction motor drive.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.33-42
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• 2010

The induction motor drive applied to field oriented control is widely used in industry applications. However, it is deceased performance and authenticity by saturation, temperature changing, disturbance and parameters changing because modeling of induction motor is nonlinear and complex. In order to control variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper proposes self tuning PI controller based on fuzzy-neural network(FNN)-PI controller that is implemented using fuzzy control, neural network, and adaptive fuzzy controller(AFC). Also, this paper proposes estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FNN-PI, AFC and ANN controller. Also, this paper proposes the anlysis results to verify the effectiveness of controller.