Vectorial control of the SPEED of an induction motor is an advanced SPEED control method, enabling us to control torque, magnetic flux individually as that of DC motor. This paper pre3sents, the effecting factors dominating on the motor &the primarily vectorial control, leading to an advanced model of control in various &arbitrary co- ordinate systems. Finally a biased field control method with/&without SPEED sensors, introduced & simulated.

This paper describes a simple way to control the Brush Less DC Motor (BLDCM) for electrical applications. To control this machine it is generally required to measure the SPEED and position of rotor by using the sensor because the inverter phases, acting at any time, must be commutated depending on the rotor position. The position sensors make the motor system more complicated and mechanically unreliable. A method for the estimation of the SPEED and rotor position of a BLDCM is presented in this work. Fuzzy based Back EMF observer is employed to estimate the SPEED by using measurements of the stator line voltage and line current. Most existing SENSORLESS methods of the BLDC motor have low performance at transients or low SPEED range and occasionally require an additional circuit. To overcome this problem, the estimation of a back-EMF is carried out by fuzzy logic techniques to improve the performance of the system. This method proposes back-EMF observer based on fuzzy function approximation and the system state equation of the BLDC motor. The fuzzy logic technique is used to estimate the SPEED of the BLDC motor under variable and fixed condition of the back-EMF. Finally, the SPEED is controlled by using Proportional-Integral (PI) Controller with the help of fuzzy based estimation of the SPEED and rotor position. Here, fuzzy based estimation of SPEED and rotor position which is also verified with the sensor, feeds input to the PI controller which does really well for good performance.

Considering the wide usage of induction motors in various industries and the limitation of applying SPEED sensors in some cases, SENSORLESS drives have became very important and the challenge to increase the accuracy of estimation continues. This paper presents a novel method for SENSORLESS SPEED control for IM's that not only improve the estimation and SPEED tracking in DTC but also eliminate the SPEED sensor in DTC. For this purpose all needed parameters for SENSORLESS SPEED control such as stator flux, SPEED and load torque are estimated with the extended Kalman filter. In this method, noise due to system structure, voltage, and current sampling is eliminated in all the effective parameters. Simulation results show the increase in the precision of estimation and SPEED tracking.

Recently, performance improvement and SPEED control of Single-Phase Induction Motors (SPIMs) have been paid attention. These aims is required the machine SPEED. In this paper, a method is proposed to estimate the SPIMs SPEED, and then, its application in torque optimization of the machine is investigated. For this purpose, the motor SPEED is obtained in terms of the motor parameters and stator flux linkage components by use of the SPIMs equations in stationary reference frame. By obtaining the flux linkage from motor windings voltages and currents, the motor SPEED is estimated desirably. Then the estimated SPEED is used to increase the average torque, to decrease the pulsation torque and to optimize the motor torque. After that, the simulation results in condition of using the real SPEED are compared with the estimated SPEED one. The low simulation error proves the validity of the proposed method.

Permanent Magnet Synchronous Machines (PMSM) are increasingly used because of their advantages over other machines, which include compactness, high efficiency, and well developed drives.. The substitution of the position sensors by advanced algorithms embedded in the controls hardware and software has been investigated for the last couple of decades. This Paper presents the modeling, analysis, design and experimental validation of a robust sensor less control method for PMSM based on Extended Kalman Filter. The position/SPEED sensor less control scheme along with the power electronic circuitry is modeled. The performance of the proposed control is assessed and verified for different types of dynamic and static torque loads.

This paper presents a new technique based on model reference adaptive system (MRAS) observer for SENSORLESS SPEED control of Two-Phase Induction Motor (TPIM). The MRAS identification is performed by means of comparison of stator fluxes obtained from both stator and rotor equations with stator voltage and current measurements. Simulation and experimental results for a 1.1 kW TPIM set-up are presented and analysed using a dSpace system with a DS1104 controller board based on digital signal processor (DSP) TMS320F240. Simulation and experimental results at nominal, low and zero SPEEDs confirm the effectiveness of the proposed SENSORLESS SPEED controlled TPIM drive.

The weakness of the Direct Vector Control (DVC) is lack of an estimation of the flux amplitude and the rotor position with high accuracy. These quantities are sensitive to parameter variations; it is important to use a robust estimation system for estimating the rotor flux with respect to parametric uncertainties. In this paper the sliding mode SPEED SENSORLESS vector control based on the Model Reference Adaptive System (MRAS) of double stator induction motor is presented. First, the models of the double stator induction motor and the DVC are proposed. Second, the MRAS technique of the DSIM is adopted. In order to ensure a robust SENSORLESS control, the sliding mode technique for the estimation system was used. The results showed the presented estimator has a positive effect on the system behavior especially in changing the reference and/or the parameters variation.

Single-phase motors are among the most widely-used motors in low-power applications. These motors are omnipresent in residential applications and make up a majority of this sector. Previously these motors were specifically employed in constant velocities. Over time the need for SPEED control in these motors has brought this problem into focus of many research investigations. SENSORLESS control of single-phase motors is particularly appealing due to mechanical and economic considerations. In the present paper, one attempts to control motor SPEED by influencing rotor flux orientation through a vector control method and propose a new method of SPEED estimation based on extended Kalman filter algorithm. In order to estimate single-phase induction motor SPEED together with on-line rotor resistance estimation, the measurement noises have been accounted in EKF algorithm. The proposed method is validated with a simulation that includes rotor resistance changes and measurement noise.