Intelligent Control with Optimal Bandwidth Tuning and Inertia Estimation for IPMSM Drive System

• Main Authors: Wei-An Yu, 俞韋安
• Other Authors: Faa-Jeng Lin
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/mu2p59

碩士 === 國立中央大學 === 電機工程學系 === 106 === In order to achieve the optimal bandwidth at different speed commands, an online auto-tuning technique using two two-input one-output wavelet fuzzy neural networks (WFNNs) for interior permanent magnet synchronous motor (IPMSM) servo drives is proposed in this thesis. Two two-input one-output four-layer WFNNs are proposed for the online auto-tuning of the gains of a proportional-integral (PI) speed controller of the servo motor drive in order to searching the optimal bandwidth without using the information of plant parameters and the characteristics of the servo motor drive. In addition, a real-time moment of inertia identification technique using wavelet fuzzy neural network for an interior permanent magnet synchronous motor (IPMSM) servo drive is proposed in this thesis. The estimated moment of inertia will be used in the online design of an integral-proportional (IP) speed controller to achieve the gains auto-tuning of the IPMSM servo drive. The WFNN is proposed for the real-time identification of the moment of inertia of the IPMSM servo drive system in order to tune the gains of the IP speed controller online at different operating conditions. Finally, a method for the detection of mechanical resonance frequency is also developed in this thesis. The experimentation using the IPMSM servo drive based on Texas Instruments' floating point digital signal processor (DSP) TMS320F28075 is presented.