Experimental verification for cost function optimization using TOPSIS approach for predictive control of surface mounted PMSM

Abstract In this article, the selection of weight factor (WF) is improved using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based cost function (CF) optimization predictive control in surface mounted permanent magnet synchronous motor (PMSM) drive under different conditions. Basically, empirical approach used WF instinctive and consumes excess time. TOPSIS chooses a action that closest ideal action's positive solution farthest from its negative solution. Prioritizing variables CF assures choice best throughout each sampling duration. Additionally, predefined switching instants are employed depending on past optimal action, reducing computing duration suggested technique. dSPACE controller real‐time execution traditional proposed methods steady dynamic states. order verify worth TOPSIS, hardware responses were compared with DTC strategies.