Fuzzy learning enhanced speed control of an indirect field-oriented induction machine drive

Abstract

Indirect field orientation (IFO) induction machine drives are increasingly employed in industrial drive systems, but the drive performance often degrades due to machine parameter variations. In this paper, a fuzzy model reference learning control technique is applied to an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve the desired speed performance. Experimental results are presented to verify the effectiveness of the proposed control scheme.