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Speed Estimation (speed + estimation)

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Engineering100%

Selected Abstracts

Speed Estimation from Single Loop Data Using an Unscented Particle Filter

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 7 2010
Zhirui Ye
The Kalman filters used in past speed estimation studies employ a Gaussian assumption that is hardly satisfied. The hybrid method that combines a parametric filter (Unscented Kalman Filter) and a nonparametric filter (Particle Filter) is thus proposed to overcome the limitations of the existing methods. To illustrate the advantage of the proposed approach, two data sets collected from field detectors along with a simulated data set are utilized for performance evaluation and comparison with the Extended Kalman Filter and the Unscented Kalman Filter. It is found that the proposed method outperforms the evaluated Kalman filter methods. The UPF method produces accurate speed estimation even for congested flow conditions in which many other methods have significant accuracy problems. [source]

Speed estimation of induction motor drive using d -axis slot harmonics and parameter identification method

ELECTRICAL ENGINEERING IN JAPAN, Issue 2 2010
Toshihiko Noguchi
Abstract This paper describes a rotor speed estimation technique of an induction motor, which utlizes slot harmonics on the d -axis caused by permeance variation across the air gap. The frequency of the slot harmonics is a multiple of the actual rotor speed, and is proportional to the number of rotor slots. In order to extract the slot harmonics, a novel adaptive bandpass filter incorporating coordinate transformation is proposed, which is effective to estimate the rotor speed from 400 to 2000 rpm. This rotor speed estimation is applied to a field-oriented controller as well as a speed controller. In addition, performance improvement is carried out by compensating a motor parameter mismatch. Feasibility of the proposed technique is confirmed through several tests, using a prototype experimental setup. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(2): 50,58, 2010; Published online in Wiley InterScience (www. interscience.wiley.com). DOI 10.1002/eej.20901 [source]

Speed Estimation from Single Loop Data Using an Unscented Particle Filter

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 7 2010
Zhirui Ye
The Kalman filters used in past speed estimation studies employ a Gaussian assumption that is hardly satisfied. The hybrid method that combines a parametric filter (Unscented Kalman Filter) and a nonparametric filter (Particle Filter) is thus proposed to overcome the limitations of the existing methods. To illustrate the advantage of the proposed approach, two data sets collected from field detectors along with a simulated data set are utilized for performance evaluation and comparison with the Extended Kalman Filter and the Unscented Kalman Filter. It is found that the proposed method outperforms the evaluated Kalman filter methods. The UPF method produces accurate speed estimation even for congested flow conditions in which many other methods have significant accuracy problems. [source]

Speed estimation of induction motor drive using d -axis slot harmonics and parameter identification method

ELECTRICAL ENGINEERING IN JAPAN, Issue 2 2010
Toshihiko Noguchi
Abstract This paper describes a rotor speed estimation technique of an induction motor, which utlizes slot harmonics on the d -axis caused by permeance variation across the air gap. The frequency of the slot harmonics is a multiple of the actual rotor speed, and is proportional to the number of rotor slots. In order to extract the slot harmonics, a novel adaptive bandpass filter incorporating coordinate transformation is proposed, which is effective to estimate the rotor speed from 400 to 2000 rpm. This rotor speed estimation is applied to a field-oriented controller as well as a speed controller. In addition, performance improvement is carried out by compensating a motor parameter mismatch. Feasibility of the proposed technique is confirmed through several tests, using a prototype experimental setup. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(2): 50,58, 2010; Published online in Wiley InterScience (www. interscience.wiley.com). DOI 10.1002/eej.20901 [source]

Tuning and parameter variation effects in MRAS based speed estimator for sensorless vector controlled induction motor drives

EUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2002
M. Wang
A frequently applied method of speed-sensorless rotor flux oriented control of induction machines relies on utilisation of model reference adaptive system (MRAS) based speed estimation, where the outputs of the reference and the adjustable model are selected as rotor flux space phasors. Accuracy of the method heavily depends on correct setting of the machine parameters and adjustment of the filter and Pl controller parameters within the estimator. The paper at first describes tuning of various parameters of the estimator, using purely experimental data. The speed estimator is operated in parallel with a commercially available rotor flux oriented induction motor drive with speed sensor and sampled stator voltages and currents are used to tune induction motor parameters, various filters and the Pl controller within the estimator. The procedure is described and illustrated using a comparison between the measured actual speed response during acceleration transients and the corresponding speed estimate obtained from the speed estimator. In the second part of the paper, speed estimation error that will take place in the base speed region due to incorrect setting and/or variation of the parameters of the machine (stator resistance, rotor resistance and magnetising inductance) within the speed estimator is assessed using experimentally recorded data. The experimental results are found to be in very good agreement with previously published theoretical results. [source]

Robust speed estimation and control of an induction motor drive based on artificial neural networks

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2008
Oscar Barambones
Abstract In this paper, a speed estimation and control scheme of an induction motor drive based on an indirect field-oriented control is presented. On one hand, a rotor speed estimator based on an artificial neural network is proposed, and on the other hand, a control strategy based on the sliding-mode controller type is proposed. The stability analysis of the presented control scheme under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally, simulated results show that the presented controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances. Copyright © 2007 John Wiley & Sons, Ltd. [source]