Abstract
This study develops an adaptive speed controller from the adaptive neuro-fuzzy inference system (ANFIS) for an indirect field-oriented (IFO) induction motor drive. First, a two-degree-of-freedom controller (2DOFC) is designed quantitatively to meet the prescribed speed command tracking and load regulation responses at the nominal case. When system parameters and operating conditions vary, the prescribed control specifications cannot be satisfied. To improve this, an adaptive mechanism combining on-line system identification and ANFIS is developed for tuning the parameters of the 2DOFC to reduce control performance degradation. With the adaptive mechanism, the desired drive specifications can be achieved under wide operating ranges. Effectiveness of the proposed controller and the performance of the resulting drive system are confirmed by simulation and experimental results.
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Chao, KH., Shen, YR. (2007). An Adaptive Speed Controller for Induction Motor Drives Using Adaptive Neuro-Fuzzy Inference System. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_38
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DOI: https://doi.org/10.1007/978-3-540-74171-8_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74170-1
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