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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xianqing Cao Liping Fan |
| Copyright Year | 2008 |
| Description | Author affiliation: Coll. of Inf. Eng., Shenyang Inst. of Chem. Technol., Shenyang (Xianqing Cao; Liping Fan) |
| Abstract | To reduce torque ripples and improve dynamic performance, a novel implementation of neural network and multi-fuzzy controller for permanent magnet synchronous motor (PMSM) direct torque controlled (DTC) drive is presented, which replaces the conventional hystersis controller with fuzzy controller (FCI) and includes a neural network speed controller (NC). To tune the weights and biases of the neural networks online, another fuzzy controller (FC2) is adopted. It combines the capability of fuzzy reasoning in handling uncertain information and the capability of neural network in learning from processes. Results of simulation are provided to demonstrate that the proposed drive has low flux linkage and torque ripples, and has quick response performance even under the occurrence of parameter variations and external disturbance. |
| Starting Page | 751 |
| Ending Page | 755 |
| File Size | 399455 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780769534978 |
| DOI | 10.1109/IITA.2008.186 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fuzzy control Programmable control Torque control Neural networks Artificial neural networks Drives Permanent magnet motors Fuzzy neural networks Adaptive control Sliding mode control |
| Content Type | Text |
| Resource Type | Article |
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