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Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

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Online identification of induction machine electrical parameters for vector control loop tuning

Telford, D. and Dunnigan, M. and Williams, B.W. (2003) Online identification of induction machine electrical parameters for vector control loop tuning. IEEE Transactions on Industrial Electronics, 50 (2). pp. 253-261. ISSN 0278-0046

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Abstract

In a vector-controlled induction machine drive, accurate knowledge of the machine electrical parameters is required to ensure correct alignment of the stator current vector relative to the rotor flux vector, to decouple the fluxand torque-producing currents and to tune the current control loops. This paper presents a new method for online identification of the induction machine parameters required to tune a rotor-flux-oriented (RFO) vector control scheme. Accuracy of the slip frequency estimation required for RFO vector control is achieved by utilizing the parameter independent 'flux pulse' rotor time constant estimation scheme, which utilizes short-duration pulses injected into the flux-producing current. The parameters required to tune the synchronous frame current control loops with a decoupling circuit are estimated using a recursive estimation scheme derived from the synchronous frame voltage equations. As the 'flux pulse' scheme requires signal injection into the flux-producing current a new rotor time constant estimation scheme is presented, based on the sensitivity analysis of the recursive parameter estimation scheme. Simulation and experimental results are presented which demonstrate the effectiveness of the online parameter identification and control loop tuning technique.