• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.216-218
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• 1995

In this article a neural network adaptive observer is proposed and applied to the case of induction motor control. The high performance vector control drives require exact knowledge of rotor flux. Because rotor time constant is needed to observe rotor flux, the accurate estimation of rotor time constant is important. For these problems, proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subject to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.269-270
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• 2013

This paper proposes the estimation algorithm to find the rotor time constant of induction motors, which is very important for induction motor drive system. This strategy is based on flux estimator theory. Proposed method has been demonstrated through simulation using MATLAB SIMULINK.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.2
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• pp.87-92
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• 2003

This paper presents a flux estimator for the sensorless vector control of induction motors. The proposed method utilize the combination of the voltage model based on stator equivalent model and the current model based on rotor equivalent model, which enables stable estimation of rotor flux in high speed region and in low speed region. The dynamic performance of proposed method is verified through the experiment. The experimental results show that motors ran easily start even under 150[%] load condition and operate continuously below 0.5[Hz].

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.34-40
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• 2012

Flux linkage of phase windings or phase inductance is an important parameter in determining the behavior of a switched reluctance motor (SRM) [1-8]. Therefore, the accurate prediction of inductance at aligned and unaligned rotor positions makes a significant contribution to the design of an SRM and its analytical approach is not straightforward due to nonlinear flux distribution. Although several different approaches using a finite element analysis (FEA) or curve-fitting tool have been employed to compute phase inductance [2-5], they are not suitable for a simple design procedure because the FEA necessitates a large amount of time in both modeling and solving with complexity for every motor design, and the curve-fitting requires the data of flux linkage from either an experimental test or an FEA simulation. In this paper, phase inductance at aligned and unaligned rotor positions is estimated by means of numerical method and magnetic equivalent circuit as well, and the proposed approach is analytically verified in terms of the accuracy of estimated inductance compared to inductance computed by an FEA simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.11
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• pp.877-887
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• 1989

In this paper, we attempt to achieve high dynamic performance by means of decoupled control of rotor speed and flux. Recently developed nonlinear feedback control theories are utilized. The rotor fluxes are estimated based on the rotor circuit equations. When the estimation error of the rotor flux tends to zero, the rotor speed and flux dynamic characteristics of the induction motor with our controller become linear. To minimize the deterioration of control performance, we use an identification algorithm for the rotor resistance. We analyze the dynamic behavior of the closed loop system with our controller. Both simulation and experimental results are included to demonstrate the practical significance of our result. In particular, our experimental results show that recently developed nonlinear feedback control techniques are of practical use in control of induction motors.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.414-427
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• 2006

This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.2
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• pp.51-58
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• 2001

This paper proposes a new strategy to estimate the rotor flux of an induction machine for the direct field oriented control. Electrical model of the induction machine presents the basic idea based on observer structure, which is composed of voltage model and current model. But the former has the defects in low speed range, the latter has the defects of sensitivity to machine parameters. In spite of these shortcomings, the closed loop flux observer based on two models has been prevalent estimation method for the direct field oriented control. In this paper, generalized analysis method named "observer characteristic function method"is proposed to analyze the kinds of the linear flux observers in unified form. With the observer characteristic function, the estimated rotor flux error involved in the classical methods can be easily clarified. Moreover, the novel rotor flux observer based on this analysis is also presented and the effectiveness of the observer has been verified by the simulation and experimental results.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.306-309
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• 2003

This paper presents a speed estimation algorithm of Switched Reluctance Motor(SRM) using flux-linkage modeling. The basic algorithm of this scheme is based on the flux linkage characteristic according to the phase current and the rotor position. A sufficient simulation and experimental data was used for neural network training. Through measurement of the phase flux linkage and phase currents, the neural network is able to estimate the rotor position and speed. The simulation result shows some good results, and possibility of this algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.2
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• pp.155-161
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• 2005

This paper presents time a constant estimation of induction motor using MRAS(model reference adaptive system) fuzzy control. The rotor time constant is enabled from the estimation of rotor flux, which has two methods. One is to estimate it based on the stator current and the other is to integrate motor terminal voltage. If the parameters are correct, these two methods must yield the same results. But, for the case where the rotor time constant is over or under estimated, the two rotor nut estimation have different angles. Furthermore their angular positions are related to the polarity of rotor time constant estimation error. Based on these observation, this paper develops a rotor time constant update algorithm using fuzzy control. This paper shows the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.343-351
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• 2000

This paper introduces a new rotor position estimation algorithm for the Switched Reluctance Motor, based on the magnetizing curves only at aligned and unaligned rotor positions. The flux linkage is calculated by measured data from phase voltage and phase current, and calculated data are used as the input of magnetizing profiles for rotor position detection. The fuzzy flux observer using novel knowledge-based fuzzy controller are presented to achieve sensorless control of the SRM. The method for selecting optimal angle is proposed for the rotor position detection. The robustness of the proposed algorithm is proved through the comparison of the simulation and experimental results.