SPEED CONTROL APPROACH OF THE PERMANENT-MAGNET SYNCHRONOUS MOTOR USING AUTOMATIC GENERATION FUZZY NEURAL NETWORK CONTROLLER

• Main Authors: Ming-Hung Chang, 張明弘
• Other Authors: Hung-Ching Lu
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/69043319566167397621

碩士 === 大同大學 === 電機工程學系(所) === 94 === This thesis presents the design and implementation of an Automatic Generation Fuzzy Neural Network (ADFNN) controller suitable for real-time control of the speed control of the permanent-magnet synchronous motor (PMSM) to track periodic step and sinusoidal reference inputs. The structure and parameter learning are done automatic and online. The structure learning is based on the partition of input space, and the parameter learning is based on the supervised gradient decent method using a delta law. Several simulation results are provided to demonstrate fast learning rate and accurate tracking performance of the proposed ADFNN control stratagem under the occurrence of parameter variations and external disturbance.