In the recent years, the use of model predictive control in electrical drives has been widely reported both theoretically and experimentally. Predictive torque control has been developed to control induction motor drives, allowing high performance and fast dynamics. However, the optimization used in predictive torque control is based on a single cost function minimization, where control objectives are merged by using weighting factors. The selection of these scalar factors is achieved through offline and online search methods and they are heavily dependent on the system parameters. To avoid this drawback, a multiobjective fuzzy predictive torque control is presented. The proposed strategy replaces the minimization of a scalar cost function with a multiobjective optimization using fuzzy decision making. Experimental implementation is presented to validate the performance of the proposed control scheme.
Áreas temáticas de ASJC Scopus
- Ingeniería eléctrica y electrónica