Akademik Veri Yönetim Sistemi
VI. International Turkic World Congress on Science and Engineering, Baku, Azerbaycan, 19 - 21 Aralık 2024, cilt.1, ss.12-23
The model predictive control (MPC) method is one of the high-performance control methods used in induction motor (IM) drives, and predictive torque control (PTC) is one of the most preferred MPC strategies for electric drives. However, the weighting factor associated with the stator flux error in the cost function must be appropriately adjusted to obtain high-performance control. In this paper, to increase the robustness and performance of the drive system, the lightning search algorithm (LSA) is used to optimize both the weighting factor of the cost function and the parameters of the proportional-integral (PI) controller used in the outer speed control loop. The LSA optimizes these parameters by utilizing a cost function based on speed errors. The optimized PTC-based IM drive system is verified in simulation with a comprehensive scenario. The average switching frequency, current harmonics, torque ripple, flux ripple, and mean square error values are also presented regarding the comprehensive test scenario. Simulation results prove the effectiveness of the optimized PTC-based IM drive.