• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.454-457
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• 2004

In this paper, control method proposed for effective speed control of the induction motor indirect vector control. For the induction motor drive, indirect vector control scheme that controls torque current and flux current of the stator current independently so that it can have improved dynamics. Also, neuro-fuzzy algorithm employed for torque current control in order to optimal speed control The proposed neuro-fuzzy algorithm can be applied to the precise speed control of an induction motor drive system or the field of any other power systems.

• 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.

• Journal of the Korean Society of Safety
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• v.16 no.4
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• pp.88-95
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• 2001

Stator core loss has significant adverse effects when an induction motor is controlled by the conventional vector control method. Therefore, taking core toss into account should make it possible to control the torque very precisely. This paper proposes a speed sensorless vector control method for an induction motor at optimum efficiency and high response taking core loss account. The proposed vector control system consists of a speed adaptive rotor flux observer which takes core loss into account and employs a direct vector control which compensates for the influence of core loss. Also, in this paper, a vector controlled induction motor with a deadbeat rotor flux controller is developed. The method ensures optimum efficiency in the steady state without degradation of the dynamic response. The validity of the proposed technique is confirmed by simulation results for induction motor drive system.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.987-992
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• 1992

In recent years, induction motor is applied for several industrial actuatung parts instead of direct current motor because of the robust construction, nonexpensive and maintenance-free actuator etc. and having capability of speed control according to development of power electrounics and microprocessor techniques. In the paper, a microprocessor-based digital control approach for spped control of induction motor system is presented by considering a simple modelling equation as the system expression equation of induction motor and using the self tuning control and torque effdforward control method. As the model equation of the induction motor system, we use a second order differential equation which is well known in the modeling equation is induced form the control theory stand point such tath we can describe usually the motor system connected by inverter, generator and load etc. The effectiveness of the control system composed by the above mentioned design concept is illustrated by the expermental result in the presence of step reference change and generator load variation.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.66-68
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• 1997

In this paper, our interest is the identification and control of nonlinear dynamic plant, induction motor, by using neural networks. We usually use vector control in the induction motor such as in the DC motor. When we go over the inputs of voltage source invertor, we can find that torque current and flux current couple each other in the induction motor. Before putting control inputs in the system, we should remove the coupling terms which we already know from them. But we should consider that cross coupling terms have time-varying variables. In this paper, we identified the parameter of induction motor by using neural networks and designed the controller with identified parameters. Through this procedure we obtained compensated inputs which are decoupled each other. Using induction motor currents control, we can make the d axis current hold constant value and control the q axis current at the same time.

• The Transactions of the Korean Institute of Power Electronics
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• v.1 no.1
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• pp.27-37
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• 1996

This paper proposes the control algorithm for maximum efficiency drive of PWM inverter - induction motor system with high dynamic performance. If the induction motor is driven under light load with rated magnetizing current, the Iron loss is excessively large compared with the codder loss which results in doer motor efficiency. Maximum efficiency drive of an induction motor can be achieved by controlling the magnetizing current to satisfy the optimal ratio that leads the total motor loss to be a minimum value at a given speed. The proposed control algorithm essentially uses vector control technique and adopts voltage decoupling control strategy to prevent the degradation of dynamic performance due to reduced magnetizing current. To verify the proposed method, digital simulations and experiments are carried out for a squirrel-cage induction motor with the rating of 2.2[kW].

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.640-643
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• 1997

This paper describes speed controller of a induction motor for electric vehicles using PLL and Fuzzy logic. The proposed system is combined precise speed control of PLL and robust, fast speed control of Fuzzy logic. The motor speed is adaptively incremented or decremented toward the PLL locking range by the Fuzzy logic using information of sampled speed errors and then is maintained accurately by PLL. The results of experiment show excellence of proposed system and that the proposed system is appropriates to control the speed of induction motor for electric vehicles.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.6
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• pp.830-836
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• 2012

Various control algorithms have been proposed for the speed-sensorless control for an induction motor. These control schemes are mainly based on the speed feedback with the flux and speed estimations. This paper proposes another method for the speed-sensorless control for an induction motor. The proposed scheme is based on the torque and flux compensation without speed estimations, in which the same controlled stator voltage is applied to both the induction motor and the numerical model so that the differences between torques and fluxes of the model and the induction motor may be compelled to give access to zero. The results of experiment show the effectiveness of the scheme.

• Journal of Power Electronics
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• v.4 no.3
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• pp.127-137
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• 2004

This paper introduces a hybrid induction motor control using a genetically optimized pseudo-on-line method. Optimization results from the use of a look-up table based on genetic algorithms to find the global optimum of an unconstrained optimization problem. The approach to induction motor control includes a pseudo-on-line procedure that optimally estimates parameters of a fuzzy PID (FPID) controller. The proposed hybrid genetic fuzzy PID (GFPID) controller is applied to speed control of a 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed controller performs better than conventional FPID and PID controllers. The contribution of this paper is the introduction of a high performance hybrid form of induction motor control that makes on-line and real-time control of the drive system possible.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.437-442
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• 2005

In order to realize the speed control of an induction motor, the information of the rotor speed is needed. So the speed sensor as an encoder or a pulse generator is used to obtain it. But the use of speed sensor occur the some problems in the control system of an induction motor. To solve the problems, the appropriate speed estimation algorithm is used instead of the speed sensor. Also there is the limitation to improve the speed control performance of an induction motor using the existing speed estimation algorithm. Therefore, in this paper, intelligent speed estimator using Fuzzy-Neural systems as adaptive laws in Model Reference Adaptive System is proposed so as to improve the existing estimation algorithm and ,using the rotor speed estimated by the Proposed estimator, the speed control of an induction motor without speed sensor is performed. The computer simulation and the experiment is executed to prove the performance of the speed control system usinu the proposed speed estimator.