| Autor: |
Shuen-Jeng Lin, Chia-Chang Tong, Yao-Lun Liu, Wu-Shun Jwo |
| Rok vydání: |
2007 |
| Předmět: |
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| Zdroj: |
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society. |
| DOI: |
10.1109/nafips.2007.383852 |
| Popis: |
The main propose of this article is to design an intelligent neural-fuzzy controller for hybrid motorcycle. A self-tuning PID tracking controller based on RBF neural network with Fuzzy current limiter is proposed to maneuver the motor and save some energy in hybrid mode. The outer motor control loop is designed to track down the speed fluctuations by Neural-PID controller. Besides, one inner loop is designed to limit the armature current whenever the power demand is diminished according to a set of Fuzzy rules. The proposed structure is put into tests by Matlab programming. Simulations confirm this RBF-PID controller with Fuzzy current limiter can save 23.5% energy for a tracking task. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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