ANALYSIS OF VECTOR CONTROLLED INDUCTION MOTOR DRIVE

Abstract

Modern method of static frequency conversion has liberated the induction motor from its historical role as a fixed speed machine. With the advancement of variable frequency drives many controlling techniques have been emerged into the field. In this work, first scalar or v/f control technique has been implemented with sinusoidal PWM inverter. Though it is simple control, but not accurate for load disturbances. To overcome this disadvantage vector control comes into picture. Of the two vector control techniques indirect vector control (IVC) is advantageous. Thus indirect vector control has been simulated and analyzed. Indirect vector control shows high dynamic performance compared to scalar control. In this work to get torque command from the speed error conventional PI controller is used. Even though PI controller works properly, but it suffers from peak overshoot and not that robust for parameter variation. Then in place of PI controller Fuzzy controller is used. Both PI and Fuzzy controller gains are optimized with Genetic Algorithm. The advantage of tuning with genetic algorithm has the ability of choosing controller gains which optimize the drive performance base on multi objective criterion without tripping in a local minima solution. The fitness function used to evaluate the individuals of each generation is integral time of absolute error (ITAE). Fuzzy controller is robust and eliminates problems that come with PI controller. Later PI .controller is replaced with ANN and drive performance is analysed. In indirect field-oriented control of induction motors, knowledge of rotor speed is required in order to orient the injected stator current vector and to establish speed loop feedback control. Tacho generators or digital shaft-position encoders are usually used to detect the rotor speed of motors. These speed sensors increase cost. In addition, for some special applications such as very high-speed motor drives, there exist difficulties in mounting these speeds sensors. With this objective, speed can be estimated using sensed stator currents and the reconstructed stator voltages.