This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct...

This paper presents a new rotor flux oriented linearizing control with speed estimation scheme for adjustable speed induction motor (IM) drive. In this scheme, rotor flux oriented vector control is used to linearize the IM drive, and decouple torque and flux. Also, a stator flux based flux estimator is used to estimate the synchronous speed. The motor speed is estimated by measuring only two li...

This paper presents a new approach to the sensorless control of the switched-reluctance motor (SRM). The basic premise of the method is that an Artificial Neural Network (ANN) forms a very efficient mapping structure for the nonlinear SRM. Through measurement of the phase flux linkages and phase currents the neural network is able to estimate the rotor position, thereby facilitating elimination...

In wind farms, individual turbines disturb the wind field by generating wakes that influence other turbines in the farm. From a control point of view, there is an interest in dynamic optimization of the balance between fatigue and production, and an understanding of the relationship between turbines manifested through the wind field is hence required. This paper develops models for this relatio...

A speed estimation method is presented in this paper for a grid-connected doubly-fed slipring induction machine drive. The proposed method is formulated with reactive power based model reference adaptive system (MRAS). The method does not require the estimation of stator/rotor flux. So, the integrator related problems at synchronous speed are overcome. Also, the estimation method is independent...

The paper presents a synthesis of an extended Gopinath observer (EGO) and analyzes the asymptotic stability of a squirrel-cage induction motor vector control system with an EGO in its loop. The considered control system is based on the direct rotor flux orientation method (DFOC) and the study of stability is based upon the linearization theorem applied around the equilibrium points of the contr...

The conventional induction motor rotor flux observer based on current model and voltage are sensitive to parameter uncertainties. In this paper, a non-parametric estimator feed-forward neural network is proposed. This operating without parameters therefore it independent from trained using Levenberg-Marquardt algorithm offline. All the data collection, training testing process fully performed i...

This paper deals with the recursive optimum estimation of rotor resistance, inductance and stator resistance of induction motor. The estimation of parameter and states in the presence of system noise is achieved using EKF, which takes in to account measurement and modelling inaccuracies. A major limitation in the parameter estimation using EKF is that its optimality is dependent on the choice o...

In general, the conventional techniques like loop impedance and nodal admittance methods are used to find the parameters of SEIG for finding performance under various conditions. In these approaches, long mathematical calculations are involved. With the recent development, ANN and fuzzy logic are used for finding various parameters for different values of machine parameters. By finding these pa...