• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.79-86
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• 2005

In this paper, an estimator scheme for the rotor speed and flux of an induction motor is proposed on the basis of a fourth-order electrical model. It is assumed that only the stator currents and voltages are measurable, and that the stator currents are bounded. There are a number of common terms in the motor dynamics, and this is utilized to find a simple error model involving some auxiliary variables. Using this error model, the state estimation problem is converted into a parameter estimation problem assuming that the rotor speed is constant. Some stability properties are given on the basis of Lyapunov analysis. In addition, the rotor resistance, which varies with the motor temperature, can also be estimated within the same framework. The effectiveness of the proposed scheme is demonstrated through computer simulations and experiments.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.3
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• pp.66-73
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• 2008

This paper presents a position sensorless control system of SRM over wide speed range. Due to the doubly salient structure of the SRM, the phase inductance varies along with the rotor position. Most of the sensorless control techniques are based on the fact that the magnetic status of the SRM is a function of the angular rotor position. The rotor position estimation of the SRM is somewhat difficult because of its highly nonlinear magnetizing characteristics. In order to estimate more accurate rotor position over wide speed range, Neural Network is used for this highly nonlinear function approximation. Magnetizing data patterns of the prototype 1-hp SRM are obtained from locked rotor test, and used for the Neural Network training data set. Through measurement of the flux-linkage and phase currents, rotor position is able to estimate from current-flux-rotor position lookup table which is constructed from trained Neural Network. Experimental results for a 1-hp SRM over 16:1 speed range are presented for the verification of the proposed sensorless control algorithm.

• Journal of Power Electronics
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• v.14 no.3
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• pp.564-571
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• 2014

Rotor initial position is an important factor affecting the control performance of electrically excited synchronous motors. This study presents a novel method for estimating rotor initial position based on sliding discrete Fourier transform (sDFT). By injecting an ac excitation into the rotor winding, an induced voltage is generated in stator windings. Through this voltage, the stator flux can be obtained using a pure integral voltage model. Considering the influence from a dc bias and an integral initial value, we adopt the sDFT to extract the fundamental flux component. A quadrant identification model is designed to realize the accurate estimation of the rotor initial position. The sDFT and high-pass filter, DFT, are compared in detail, and the contrast between dc excitation and ac injection is determined. Simulation and experimental results verify that this type of novel method can eliminate the influence of dc bias and other adverse factors, as well as provide a basis for the control of motor drives.

• Journal of Power Electronics
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• v.16 no.6
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• pp.2150-2161
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• 2016

Mechanical and electrical parameter uncertainties cause dynamic and static estimation errors of the rotor speed and position, resulting in performance deterioration of sensorless control systems. This paper applies an extended nonlinear observer to interior permanent magnet synchronous motors (IPMSM) for the simultaneous estimation of the rotor speed and position. Two compensation methods are proposed to improve the observer performance against parameter uncertainties: an on-line rotational inertia adjustment approach that employs the gradient descent algorithm to suppress dynamic estimation errors, and an equivalent flux error compensation approach to eliminate static estimation errors caused by inaccurate electrical parameters. The effectiveness of the proposed control strategy is demonstrated by experimental tests.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.212-218
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• 2007

This paper presents a implementation of speed sensorless vector control of induction motor using MATLAB/SIMULINK and dSPACE DS1104. Proposed flux estimation algorithm, which utilize the combination of the voltage model based on stator equivalent model and the current model based on rotor equivalent model, enables stable estimation of rotor flux. Proposed rotor speed estimation algorithm utilizes the estimated flux. And the estimated rotor speed is used to speed control of induction motor. Overall system consists of speed controller, current controller, and flux controller using the most general PI controller. Speed sensorless vector control algorithm is implemented as block diagrams using MATLAB/SIMULINK. And realtime control is performed by dSPACE DS1104 control board and Real-Time-Interface(RTI).

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.36-39
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• 2002

This paper presents a simulation results of sensorless control of Switched Reluctance Motor(SRM) using neural network. 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 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. The simulation result shows some good results, and possibility of this algorithm.

• Journal of Magnetics
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• v.18 no.1
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• pp.57-64
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• 2013

Flux linkage of phase windings is a key parameter in determining the behavior of a switched reluctance motor (SRM) [1-8]. Therefore, the accurate prediction of flux linkage 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 saturation in flux. Although several different approaches using a finite element analysis (FEA) or a curve-fitting tool have been employed to compute phase flux linkage [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 flux linkage at aligned and unaligned rotor positions is estimated by means of a reluctance network, and the proposed approach is analytically verified in terms of accuracy compared to FEA.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1161-1164
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• 2002

The position information of the rotor are required while the SRG(Switched Reluctance Generator) is drived. The position information is generally provided by shaft encoder or resolver. But it is weak in the dusty, high temperator and EMI environment. Therefore, It is required for the sensor to be eliminated from SRG. In this paper, a estimation algorithm for the rotor position of the SRG is introducted and a constant DC-link voltage is controled by PID controller. The estimation algorithm is imple--mened by using the instantaneous flux profile, and the initial position is estimated by injecting high frequency pulse voltage. It is proved that the rotor position is esti--mated very well by the exeriments.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.253-263
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• 2002

This paper presents an adaptive feedback linearization control scheme for induction motors using stator fluxes. By using stator flukes as states, overparameterization is prevented and control inputs can be determined straightforwardly unlike in existing schemes. This approach leads to the decrease of the relative degree for the flux modulus and thus yields a simpler control algorithm than the prior results. In this paper. adaptation schemes are suggested to compensate for the variations of stator resistance. rotor resistance and load torque. In particular, the adaptation to the variation of stator resistance with a feedback linearization control is a new trial. In addition, to improve the convergence of rotor resistance estimation, the differences between stator currents and its estimates are used for the parameter adaptation. The simulations show that torque and flux are controlled independently and that the estimates of stator resistance, rotor resistance, and load torque converge to their true values. Actual experiments on a 3.7㎾ induction motor verify the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.510-513
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• 1996

This paper consists of the speed sensorless vector control of induction motors with the estimation of rotor resistance. In the application of variable-speed induction motor drives, if an inaccurate rotor resistance is used because the rotor resistance can change due to skin effects and temperature variables, it is difficult to achieve a collect field orientation. In this paper, to overcome these difficulties adaptive algorithm is designed for rotor resistance identification at the beginning of the transient state. And an adaptive flux observer is used for the purpose of estimating rotor flux and speed in the speed sensorless scheme. Computer simulations are carried out to verity the validity of the proposed algorithm.