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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Chao, K. H., & Shen, Y. R. (2007). An adaptive speed controller for induction motor drives using adaptive neuro-fuzzy inference system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4681 LNCS, pp. 381–393). Springer Verlag. https://doi.org/10.1007/978-3-540-74171-8_38
Mendeley helps you to discover research relevant for your work.