PhD Thesis Defense Session

Abstract:
Control of Induction motor due to it’s the nonlinear property is one of the most popular research topics recently. Vector control based algorithms which are used for proper functioning need to estimate the rotor speed and magnetic flux. In many applications, flux and speed must be estimated without using sensors. Thus, in these cases, it is necessary to obtain speed and flux by measuring voltage and current.
In this thesis, a nonlinear observer for estimating motor parameters based on Lyapunov function is presented. Using the Lyapunov theory, inputs regulating system and control system are earned which improve increases system performance.
Moreover a novel control speed sensorless indirect field-oriented control for the full-order model of the induction motor is presented. It provides local exponential tracking of smooth speed and flux amplitude reference signals together with local exponential field orientation, on the basis of stator current measurements only and under assumption of unknown constant load torque.
The absence of the flux model in the proposed algorithm allows for simple and effective time-scale separation between the speed–flux tracking error dynamics (slow subsystem) and the current error dynamics (fast subsystem). This property is exploited to obtain a high performance sensorless controller, with features similar to those of standard field-oriented induction motor drives. The theoretical analysis based on the singular perturbation method enlightens that a persistency of excitation condition is necessary for the asymptotic stability.
Extensive simulation and experimental tests confirm the effectiveness of the proposed approach. These results show the advantages of proposed observer in control of induction motor transient performances. The merits of the proposed control system are also indicated in comparison with a traditional optimal control system.

Day : Wednesday     Date: 2011/12/28    Time:15
Class : 305