Speed Sensorless Estimation of AC Induction Motors Using the Fast Orthogonal Search Algorithm

McGaughey, Donald R.; Tarbouchi, Mohammed; Nutt, K.; Chikhani, A.Y.

doi:10.1109/tec.2005.853766

Cited by 18 publications

(20 citation statements)

References 10 publications

(10 reference statements)

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“…FOS algorithm has a lot of practical applications including spectral model estimations, time series analysis and non-linear system control [19][20][21][22], and the proposed algorithm is based on FOS algorithm. The main goal of the proposed algorithm is to create a functional expansion of an input y(n) by choosing the best basis functions from all candidate functions P k (n), in order to minimize the mean squared error (MSE) between y(n) and the functional expansion.…”

Section: High Resolution Carrier Frequency Estimationmentioning

confidence: 99%

A Fine Frequency Estimation Algorithm Based on Fast Orthogonal Search (FOS) for Base Station Positioning Receivers

Deng

Jia

et al. 2018

Electronics

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Base station signals have been widely studied as a promising navigation and positioning signal. The time and code division-orthogonal frequency division multiplexing (TC-OFDM) signal is a novel communication and navigation fusion signal that can simultaneously implement communication and positioning services. The TC-OFDM signal multiplexes the pseudorandom noise (PRN) code, called positioning code, and the Chinese mobile multimedia broadcasting (CMMB) signal in the same frequency band. For positioning in the TC-OFDM receiver, it is necessary to acquire and track the PRN code phase and the carrier frequency. The tracking performance is directly influenced by the accuracy of the signal acquisition, especially the acquired carrier frequency accuracy. This paper focuses on the fine frequency acquisition of TC-OFDM receivers and proposes a novel fine frequency estimation algorithm, which uses a non-linear modelling method, called fast orthogonal search (FOS), to improve the frequency acquisition accuracy of TC-OFDM receivers. With this algorithm, the PRN code is first stripped off in coarse code phase. Then, the candidate functions at each of the interest frequencies are generated, which consist of pairs of sine and cosine terms. Finally, the FOS algorithm is used to detect the carrier frequency. Simulation and experimental results show that, compared with the current carrier frequency estimation algorithms, the proposed algorithm effectively improves carrier frequency estimation accuracy and then reduces the time to the first fix.

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Section: High Resolution Carrier Frequency Estimationmentioning

confidence: 99%

A Fine Frequency Estimation Algorithm Based on Fast Orthogonal Search (FOS) for Base Station Positioning Receivers

Deng

Jia

et al. 2018

Electronics

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“…The FOS algorithm [7,8,9] is a nonlinear technique that allows fitting of an input function y(n) of length N to a functional expansion given by (2) where p m (n) are arbitrary functions, a m are the weights of the functional expansion, and e(n) is the residual error of the model.…”

Section: Fos Algorithmmentioning

confidence: 99%

Current signature analysis of induction machine rotor faults using the fast orthogonal search algorithm

King¹,

Tarbouchi²,

McGaughey³

2010

5th IET International Conference on Power Electronics, Machines and Drives (PEMD 2010)

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This paper presents a method of detecting rotor faults in induction motors using the fast orthogonal search (FOS). Proper online monitoring of motors is important to ensure safe operation, timely maintenance, and efficiency. One method to detect rotor faults is to monitor the stator current spectrum for fault harmonics. Conventional methods that use the FFT for spectral analysis are inadequate for motors that are prone to transient conditions. Changing operating conditions during the sampling time may cause the spectrum to become smudged, reducing the amplitude of the fault signatures causing them to become undetectable. Reducing the sampling time minimizes the effects of smudging, however a fine resolution must still be maintained to distinguish between harmonics. This is especially important when operating under light-load since the fault signatures will be very close to the fundamental frequency. Therefore a balance between resolution and sampling time must be achieved, which is difficult with the FFT. This paper will demonstrate through simulation that FOS is able to achieve eight times the resolution of the FFT for the same data length. Therefore FOS is a promising choice for rotor fault detection in motors where long periods of steady-state are unavailable, and for motors operating with less than full-load.

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“…Computer-based real-time applications using fieldprogrammable gate array (FPGA) based hardware present attractive possibilities for enhancing real-time performance of electric drive systems. Compared to microcontroller systems traditionally employed to enable real-time applications in electric drives [1][2][3][4], FPGAs generally provide the advantages of a significantly more flexible architecture with unconstrained input/output interfaces, high compatibility levels across different platforms and increased processing speed. While realtime FPGA based solutions have been researched for implementation of drive control algorithms [5][6] they received significantly less attention where drive parameter estimation techniques are concerned [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Real-time frequency tracking for induction motor drives using LabVIEW FPGA

Tshiloz

Djurović

2017

2017 6th Mediterranean Conference on Embedded Computing (MECO)

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This paper reports the implementation procedure of a real-time frequency tracking algorithm for induction motor drive velocity estimation on a commercial cRIO real-time/FPGA platform. The general software architecture required to establish a real-time frequency tracking routine is presented and its frequency tracking performance illustrated in practical tests on a 7.5 kW induction motor drive. The presented architecture is shown to provide a flexible and effective platform for real-time frequency estimation applications in electric motor drives.

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Speed Sensorless Estimation of AC Induction Motors Using the Fast Orthogonal Search Algorithm

Cited by 18 publications

References 10 publications

A Fine Frequency Estimation Algorithm Based on Fast Orthogonal Search (FOS) for Base Station Positioning Receivers

A Fine Frequency Estimation Algorithm Based on Fast Orthogonal Search (FOS) for Base Station Positioning Receivers

Current signature analysis of induction machine rotor faults using the fast orthogonal search algorithm

Real-time frequency tracking for induction motor drives using LabVIEW FPGA

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