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http://dx.doi.org/10.6113/JPE.2015.15.5.1274

MRAS Based Speed Estimator for Sensorless Vector Control of a Linear Induction Motor with Improved Adaptation Mechanisms  

Holakooie, Mohammad Hosein (Department of Electrical and Computer Engineering, University of Tabriz)
Taheri, Asghar (Department of Electrical Engineering, University of Zanjan)
Sharifian, Mohammad Bagher Bannae (Department of Electrical and Computer Engineering, University of Tabriz)
Publication Information
Journal of Power Electronics / v.15, no.5, 2015 , pp. 1274-1285 More about this Journal
Abstract
This paper deals with model reference adaptive system (MRAS) speed estimators based on a secondary flux for linear induction motors (LIMs). The operation of these estimators significantly depends on an adaptation mechanism. Fixed-gain PI controller is the most common adaptation mechanism that may fail to estimate the speed correctly in different conditions, such as variation in machine parameters and noisy environment. Two adaptation mechanisms are proposed to improve LIM drive system performance, particularly at very low speed. The first adaptation mechanism is based on fuzzy theory, and the second is obtained from an LIM mechanical model. Compared with a conventional PI controller, the proposed adaptation mechanisms have low sensitivity to both variations of machine parameters and noise. The optimum parameters of adaptation mechanisms are tuned using an offline method through chaotic optimization algorithm (COA) because no design criterion is given to provide these values. The efficiency of MRAS speed estimator is validated by both numerical simulation and real-time hardware-in-the-loop (HIL) implementations. Results indicate that the proposed adaptation mechanisms improve performance of MRAS speed estimator.
Keywords
Adaptation mechanism; Fuzzy controller; Linear induction motor (LIM); Mechanical model; Model reference adaptive system (MRAS); Vector control;
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