Direct Torque Control Based on Space Vector Modulation with Adaptive Neural Integrator for Stator Flux Estimation in Induction Motors

Direct torque control based on space vector modulation (SVM-DTC) preserve DTC transient merits, furthermore, produce better quality steady-state performance in a wide speed range. A new adaptive neural integration algorithm for estimating stator flux is introduced. The simulations of conventional DTC and the proposed control topologies are given and discussed. It is concluded that the proposed control topology outperforms the conventional DTC in reducing torque ripple and eliminating bad effect of dc-offset.