• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.3
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• pp.117-126
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• 2012

This study configuration Vector Control System which is stable and has outstanding Dynamic Characteristics in Very Low Speed Region and Low Speed Region, and proposes Instantaneous Speed Observer and Very Low Speed Control method using Reduced-Dimensional State Observer. The Observer proposed in this system, by appling Reduced-Dimensional State Observer to Load-Torque estimation and using for speed estimation, implements system composition simply and is capable of accurate Instantaneous Speed estimation in Very Low Speed Region. Also, this study reduces influence by System Noise and suggests an induction motor speed control system which is effective in Load Disturbance, modeling error, estimation noise and so on without changing pole of an Observer.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.359-365
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• 2005

The absolute longitudinal speed of a vehicle is estimated by using data from an accelerometer of the vehicle and wheel speed sensors of a standard 50-tooth antilock braking system. An intuitive solution to this problem is, 'When wheel slip is low, calculate the vehicle velocity from the wheel speeds; when wheel slip is high, calculate the vehicle speed by integrating signal of the accelerometer.' The speed estimator weighted with fuzzy logic is introduced to implement the above concept, which is formulated as an estimation method. And the method is improved through experiments by how to calculate speed from acceleration signal and slip ratios. It is verified experimentally to usefulness of estimation speed of a vehicle. And the experimental result shows that the estimated vehicle longitudinal speed has only a $6\%$ worst-case error during a hard braking maneuver lasting a few seconds.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.1
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• pp.37-46
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• 2004

A novel rotor speed estimation method using model reference adaptive control(MRAC) is proposed to improve the performance of a sensorless vector controller. In the proposed method, the stator current is used as the model variable for estimating the speed. In conventional MRAC methods, the relation between the two model errors and the speed estimation error is unclear. In the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation. The robustness of the rotor flux-based MRAC, back EMF-based MRAC, and proposed MRAC is compared based on a sensitivity function about each error of stator resistance, rotor time constant, mutual inductance. Consequently, the proposed method is much more robust than the conventional methods as regards errors in the mutual inductance, stator resistance. Therefore, the proposed method offers a considerable improvement in the performance of a sensorless vector controller at a low speed. In addition, the superiority of the proposed method and the validity of sensitivity functions were verified by simulation and experiment.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.96-102
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• 1999

Sensorless speed estimation in induction motor systems is one of the most control engineers. Based on the estimated speed the vector control has been applied to the high precision torque control however most speed estimation methods use adaptive scheme so that it takes long time to estimate the speed. Thus the adaptive estimation scheme is not effective to the induction motor which requires short sampling time. In this paper a new linearized equation of induction motor system is proposed and a sensorless speed estimation algorithm based on observation techniques is developed. First the nonlinear induction motor equation is linearized at an equilibrium point. Second a proportional integral(PI) observer is applied to estimate the speed state in the induction motor system. Finally simulation results will assure the effectiveness of the new linearized equation and the sensorless estimation algorithm by using PI observer in the nonlinear induction motor system.

• Journal of IKEEE
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• v.22 no.2
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• pp.460-475
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• 2018

In the variable-speed wind energy system, to achieve maximum power point tracking (MPPT), the wind turbine should run close to its optimal angular speed according to the wind speed. Non-linear control methods that consider the dynamic behavior of wind speed are generally used to provide maximum power and improved efficiency. In this perspective, the mechanical power is estimated using Kalman filter. And then, from the estimated mechanical power, the wind speed is estimated with Newton-Raphson method to achieve maximum power without anemometer. However, the blade shape and air density get changed with time and the generator efficiency is also degraded. This results in incorrect estimation of wind speed and MPPT. It causes not only the power loss but also incorrect wind resource assessment of site. In this paper, the adaptive maximum power point tracking control algorithm for wind turbine system based on the estimation of wind speed is proposed. The proposed method applies correction factor to wind turbine system to have accurate wind speed estimation for exact MPPT. The proposed method is validated with numerical simulations and the results show an improved performance.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.288-293
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• 2008

A predictive model of wind speed in the wind farm has very important meanings. This paper presents an estimation model of wind speed based on time series analysis using the observed wind data at Hangyeong Wind Farm in Jeju island, and verification of the predictive model. In case of Hangyeong Wind Farm and Haengwon Wind Farm, The ARIMA(Autoregressive Integrated Moving Average) predictive model was appropriate, and the wind speed estimation model was developed by means of parametric estimation using Maximum likelihood Estimation.

• Journal of Power Electronics
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• v.5 no.4
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• pp.282-288
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• 2005

In this paper, a new speed sensorless induction motor scheme which can estimate rotor speed and rotor resistance simultaneously is presented. The rotor flux with a low frequency sinusoidal waveform is used to conduct on-line simultaneous estimation of the rotor speed and rotor resistance. Hence the proposed sensorless control method is robust to rotor resistance variations. Also, the control scheme has no current minor loop to determine voltage references. It contributes to good control performance at low speeds. Some simulation results supported by experiments are given to show the effectiveness of this method.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.1123-1133
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• 2012

This study configuration Vector Control System which is stable and has outstanding Dynamic Characteristics in Very Low Speed Region and Low Speed Region, and proposes Instantaneous Speed Observer and Very Low Speed Control method and vector control system of the speed estimation a using Reduced-Dimensional State Observer. The Observer proposed in this system, by appling Reduced-Dimensional State Observer to Load-Torque estimation and using for speed estimation, implements system composition simply and is capable of accurate Instantaneous Speed estimation in Very Low Speed Region. Also, this study reduces influence by System Noise and suggests an induction motor speed control system which is effective in Load Disturbance, modeling error, estimation noise and so on without changing pole of an Observer.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.692-699
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• 2003

A novel rotor speed estimation method using Model Reference Adaptive Control(MRAC) is proposed to improve the performance of a sensorless vector controller. In the proposed mettled, the stator current is used as the model variable for estimating the speed. In conventional MRAC methods, the relation between the two model errors and the speed estmation error is unclear. Yet, in the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation and is robust to the parameters error In addition, the proposed method of offers a considerable improvement in the performance of a sensorless vector controller at a low speed. The superiority of the proposed method is verified by simulation and experiment in a low speed region and at a zero-speed.