Quantum Evolutionary Algorithm based fast speed controlled induction motor drive with CRTRL flux estimator

This paper proposes the Quantum Evolutionary Algorithm (QEA) based fast speed response controller tuning for induction motor drive. Here the proportional and integral gains of PI controller are optimized by QEA to achieve quick speed response. A simple rotor flux estimator based on Correlated Real Time Recurrent Learning (CRTRL) algorithm is proposed for high performance induction motor drive. Simulation tests have been conducted to study the dynamic performances of the drive system for both the Conventional Genetic Algorithm (CGA) based PI and QEA based PI controllers. The proposed method shows better control performance than CGA based induction motor drive under transient and steady state conditions.