Adaptive Speed Prediction for Direct Torque-controlled Permanent Magnet Synchronous Motor Drive Using Elephant Herding Optimization Algorithm.

In this study, an adaptive speed prediction scheme based on reactive power was established for direct torque-controlled (DTC) permanent magnet synchronous motor (PMSM) drives. The current and flux of a stator were used to establish a DTC PMSM drive. Hall effect current sensors with a non-contact sensing technique were used to detect the stator current of the PMSM. The voltage space vector pulse width modulation (VSVPWM) DTC scheme was used in place of a traditional switching table (ST) DTC scheme to reduce current and torque ripples. Model reference adaptive control (MRAC) was utilized to develop a speed prediction scheme, and its adaptation mechanism was designed using the elephant herding optimization (EHO) algorithm. The torque, flux, and speed controllers were designed using a proportional–integral (P–I)-type controller. The MATLAB/Simulink© toolbox was used to establish the simulation scheme, and all control algorithms were realized using a microprocessor control card. The simulation and experimental results confirmed the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]