Abstract
Model predictive control (MPC) is the result of the latest advances in power electronics and modem control. It is regarded as one of the best techniques when it comes to handling of nonlinearities in the intrinsic model of induction motor (IM). Conventional MPC utilizes weighting factors in the objective function that are tuned after rigorous experimental work which can be improved by utilizing the more mature intelligent optimization techniques like NSGA-II etc. In this study, the weighting factor optimization for the conventional MPC control of IM based on NSGA-II with TOPSIS decision-making criteria is studied. A control algorithm is designed, and an experimental test setup is made to obtain the results of this intelligent MPC which are compared with conventional MPC based on some performance indices like torque and flux ripple, switching frequency loss etc.
Highlights
The fundamental difference of electrical drive systems to mechanical systems is the ease of control, their spontaneous startup and fully-loaded with a simple command from even a remote location
The latest work on weighting factor optimization for FCS-MPTC was reported in [32] where the author applied the NSGA-II to find the Pareto optimal front for optimal weighting factors and evaluate each solution based on switching loss, total harmonic distortion, torque and flux ripple performance criteria
FCS-MPTC sampling rate was fixed at 20 kHz which was same as the sampling frequency for the entire model
Summary
The fundamental difference of electrical drive systems to mechanical systems is the ease of control, their spontaneous startup and fully-loaded with a simple command from even a remote location. In conventional DTC, for each control cycle, an appropriate voltage vector is selected from the all intrinsic vectors of the inverter in accordance to the two control outputs of hysteresis controllers (comparators) to generate gate signals for the inverter This feature leads to the drawbacks of irregular torque and flux pulsations together with additional harmonic losses. Reducing the torque and flux ripple levels of the conventional DTC system while retaining its intrinsic merits has become a subject of intense research [11] In contrary to these mainstream control techniques there is a growing more efficient control technique (based on the discrete model of induction motor) known as Model Predictive Control.
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