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Content Provider | IEEE Xplore Digital Library |
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Author | Zhonghua Fan Shihua Li |
Copyright Year | 2012 |
Description | Author affiliation: School of Automation, Southeast University, Nanjing 210096 (Zhonghua Fan; Shihua Li) |
Abstract | The vector control method is often applied to speed regulating system of Permanent Magnet Synchronous Motor (PMSM). Control period of speed loop is usually longer than that of current loop. Different regulating algorithms can be applied to speed and current loops. The difference between the control periods of two control-loops in PMSM servo is becoming smaller. Two control-loops structure can be replaced by single control-loop structure. In such a case, model predictive controller (MPC) in the single control-loop based on the second-order relationship between voltage and speed of PMSM is developed in this paper. Moreover, considering the case of large range inertia variation, adaptive model prediction control based on inertia identification is designed for PMSM speed regulation system. Simulation results show that model predictive controller designed in this paper supplies better performance of dynamic behavior and load disturbance rejection compared with model predictive controller in speed loop of two control-loops structure. Adaptive model prediction control method can restrain influence of large range inertia variation in speed regulation system. |
Starting Page | 4412 |
Ending Page | 4417 |
File Size | 436069 |
Page Count | 6 |
File Format | |
ISBN | 9781467325813 |
ISSN | 21612927 |
e-ISBN | 9789881563811 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-07-25 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Chinese Assoc of Automati |
Subject Keyword | Adaptation models MPC PMSM Single control loop Predictive models Permanent magnet motors Educational institutions Electronic mail Adaptive control Inertia identification Load modeling Periodic structures |
Content Type | Text |
Resource Type | Article |
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