Abstract
A new online identification methodology for estimation of the rotor flux components and the main electrical parameters of vector controlled induction motors is presented in this paper. The induction motor model is referred to the rotor reference frame for estimation of rotor flux and rotor parameters, and referred to the stator reference frame to estimate stator parameters. The stator parameters estimation is achieved by a prediction error method based on a model structure described by a linear regression that is independent of rotor speed and rotor parameters. The rotor flux components and rotor parameters are estimated by a reduced order extended Kalman filter, using a 4th-order state-space model structure where the state equation is described by matrices that are diagonal and independent of rotor speed as well as stator parameters. Both methods work in a boot-strap manner. © 2003 IEEE.

Abstract
In this article, we propose a linear parameterization (LP) for representing the friction in the tire-road interface, suitable for on-line Identification. This model was obtained by employing function approximation techniques, which results in an optimization problem to minimize the fitting error between the LP and the nonlinear Burckhardt model. Compared with others LPs proposed in the literature, the optimal LP features a reduced number of parameters and good approximation capabilities. Moreover, the proposed model can be identified though linear Identification techniques, simplifying the on-line peak friction estimation. Simulation results obtained with a vehicle simulator demonstrates the effectiveness of the proposed parameterization. © 2011 IFAC.

Abstract
A robust feedback control of an induction motor is proposed. The theoretical basis is a continuous-time machine model defined by a pair of simultaneous complex-coefficients differential equations. The parameter uncertainties and load perturbations are considered in the controller design. The control methodology is based on sliding mode control techniques. The design of a sliding mode controller for tracking the torque and the rotor flux of an induction motor drive is also given. The design includes the hardware structure, control laws for torque control and rotor flux control. The modulation is defined as part of the variable structure control algorithm which enables an optimum choice of the output voltage of the static converter. The validity and robustness of the proposed control system were verified by simulation. The simulation results are presented to demonstrate their agreement with the theoretical predictions of the proposed controller. Copyright (C) 2000 John Wiley & Sons, Ltd.

Abstract
This paper describe an instrument for real-time visualization of the quantities necessary for analysis, diagnosis and investigations of AC machine drives on an oscillographic display. The instruments needs no shaft position or speed sensor, it uses exclusively the acquired stator currents and voltages and provides information, in electrical and visual form of: stator and rotor flux, torque, reactive power, torque current, flux current, torque angle, slip frequency. The measuring instrument is based in analogue signal processing techniques. The main fields of application are: monitoring systems, control units, research tool for induction motor drives, and test shop. Practical results of the implementation are presented and discussed.

Abstract
This paper addresses the problem of parameter estimation of continuous-time systems using samples of its input-output data. We propose a method based on the bilinear transformation to obtain an equivalent discrete-time model. Introducing a new, polynomial pre-filter it is possible to compute the physical parameters via inverse mapping between the discrete-time and the continuous-time models. A simulation example is given to illustrate the noise effects in the parameter estimation results. Using experimental results, we demonstrate the ability of the estimator to handle real measurement problems.

Abstract
This paper presents a new approach for the simultaneous identification of rotor flux components in the rotor reference frame and electrical parameters of a vector controlled induction motor, for real-time implementations, using an extended Kalman filter (EKF) and a reduced order model structure for lower computational effort. The proposed new method requires the measurement of motor speed, stator voltages and currents signals. Using a motor model structure with four electrical parameters, the estimation of flux space phasor and rotor parameters is presented. The estimation is subsequently further extended to include the motor stator parameters and the results are analyzed as well as robustness. Simulated and experimental studies highlight the improvements brought by this new approach, mainly, a simple and reduced state equation, the introduced scalar output equation and lower computational cadency, by using lower sampling frequencies in the proposed rotor reference frame.