Vector Control Design for Induction Motors Using Takagi-Sugeno-Kang Fuzzy Speed Estimator
| Autor: | Chun-Jung Chiu, 邱俊榮 |
|---|---|
| Rok vydání: | 2009 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 97 In this thesis, the Takagi-Sugeno-Kang fuzzy theory is used to design the TSK fuzzy speed estimator and TSK fuzzy rotor resistance estimator for establishing the speed sensor-less control. Moreover, the projection algorithm in adaptive theory is adopted to modify the parameters of the TSK fuzzy rules in the consequence part. The speed and rotor resistance estimated by the proposed estimator are fed back to the adaptive fuzzy cerebellar model articulation controller (AFCMAC) and pseudoreduced-order flux observer (APRO) in order to achieve the adaptive vector control. The proposed vector control of the motor drive integrates the direct field orientation control (DFOC) and the adaptive control law. Also, an adaptive pseudoreduced-order flux observer (APRO) is used to estimate the rotor flux and solve the problem that the constants of pole assignment must be changed according the speed command; this problem often happens when the adaptive full-order flux observer (AFO) is applied. In addition, the use of APRO reduces the computation time of control algorithm. Under the operation conditions that the speed range varies from 2% to 100% of the rated speed with 8-Nm start-up torque load, the experimental results indicate that the speed not only has superior dynamic response but also remains robustness in the environment of motor parameter variations when the AFCMAC, TSK fuzzy speed estimator, and TSK fuzzy rotor resistance estimators are applied. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|