| The induction motor represents a difficult control problem. This is due to three reasons: (i) the dynamic model of the induction motor is nonlinear, (ii) the rotor electrical state variables are usually unavailable for measurement, (iii) the motor parameters can vary considerably from their nominal values with a significant effect on the system dynamics. The main purpose of this work is to develop control algorithms that force the induction motor to track predetermined speed, position and flux trajectories without having to estimate the rotor electrical state variables. This eliminates the necessity of a state estimator to calculate the inaccessible rotor electrical state variables. To achieve this, two passivity-based methods are developed. In passivity-based methods, the key point is the identification of the workless forces, that is, the terms which appear in the dynamic equations of the induction motor but do not have any effect on the energy balance equation of the induction motor. These terms do not influence the stability properties of the induction motor; therefore, there is no need to cancel them with feedback control. This leads to a simpler control structure and enhances the robustness of the control system. The passivity-based methods developed in this work consider both the linear and saturated magnetics model of the induction motor. To verify the methods experimentally, three different moves were considered. These are: (1) fast point-to-point moves, (2) speed reversal, (3) constant speed with constant load torque. These moves reflect the types of trajectories commonly found in industrial applications of electric motors. The experimental results show that the passivity-based methods provide tracking of time-varying speed, position and flux trajectories without knowledge of the rotor electrical state variables. |
