Artificial Intelligence based DTC Controlled Matrix Converter Cage Drive System

摘要

Matrix converter induction motor drive system operated with a direct torque control (DTC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic is used in conjunction with direct torque control to minimize these problems. A fuzzy logic controller chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determined by observing the vector diagram of flux and currents. The operation of the direct torque controller becomes difficult at low speeds due to the effect of change in stator resistance on the flux measurements. To improve the system performance at low speeds a fuzzy resistance estimator is proposed to eliminate the error due to the change in stator resistance. At constant flux and torque commands any change in stator resistance of the induction machines causes an error in stator current. This error is utilized by the fuzzy resistance estimator to correct the stator resistance used by the controller to match the machine resistance. Both fuzzy controller and fuzzy resistance estimator are implemented using DSP TMS320C6711 for a 3 hp induction motor drive system. Results demonstrate enhanced performance.