An interior search algorithm based on chaotic and crossover strategies for parameter extraction of polyphase induction machines

Abstract The accuracy of the extracted parameters is important for studying polyphase induction motor performance and/or control schemes. An investigated and improved interior search algorithm (IISA) presented in this study extracting optimal values estimated six-phase three-phase motors. This investigation was carried out on two motors as experimental research cases, utilizing features manufacturer's operation. show high capability regarding desired IISA optimizer. proposed compared with different modern optimization algorithms including basic ISA, other state-of-the-art approaches. Experimental verifications are validated motors, called obtained results that method very competitive unknown models a degree closeness to records. Moreover, various statistical tests, such Wilcoxon rank test, stability analysis, convergence have been conducted justify IISA. From all analyses, it has revealed popular competitors ISA variant accurately identified parameters.