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In this paper, a simple and effective algorithm for direct torque and flux control three phase induction motor drive is proposed. In this method, control technique is based on decouple between amplitude and angle of reference stator flux for determining required stator voltage vector. This proposed method eliminates the estimation of stator flux angle to generate stator voltage vector with constant...
This paper proposes an algorithm for direct flux and torque controlled sensorless three phase induction motor drive systems. This method is based on control of slip speed and decouple between amplitude and angle of reference stator flux for determining required stator voltage vector. Within the given sampling time, flux as well as torque errors are controlled by stator voltage vector which is evaluated...
This paper presents a new technique for online identification of an induction motor rotor time constant. The technique is designed for a shaft-sensorless indirect field-oriented control induction motor drive with a model reference adaptive system (MRAS)-based speed estimator. The MRAS estimator is sensitive to the changes in the rotor time constant, and on line identification of that parameter is...
Multi-phase ac motor drives are nowadays considered for various applications, due to numerous advantages that they offer when compared to their three-phase counterparts. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. This paper analyses operation of a Model Reference Adaptive System (MRAS)-based sensorless...
This paper presents the experimental validation of an efficient position control scheme, based on the speed smooth VSC (Variable Structure Control) algorithm with an adaptive gain for the indirect vector control of the induction motor. The position loop is regulated with a Proportional controller and the speed loop incorporates a smooth and adaptive VSC regulator, while in the current loops incorporates...
An induction motor with vector control has a very good dynamic behavior and as a consequence is well suited for high performance applications. But, the vector control is very sensitive to variations in the rotor time constant. In the paper there is presented signal processing for the vector control of an induction motor with rotor time constant adaptation using TMS320F2812 DSP. The method employs...
This paper presents Adaptive Neuro-Fuzzy Inference System (ANFIS) based intelligent control of vector controlled induction motor drive. The proposed intelligent control scheme consists of sensorless adaptive neuro-fuzzy speed controller with speed estimation based on adaptive neuro-fuzzy inverse model. The proposed neuro-fuzzy speed controller incorporates fuzzy logic algorithm with a five-layer artificial...
This paper presents the experimental validation for industrial applications of the new smooth VSC (variable structure control) algorithm with an adaptive gain for the indirect vector control of the induction motor. This control algorithm is used in the speed control loop, while in the current loops incorporates the SVPWM (space vector pulse width modulation) with the PI (proportional integral) controllers,...
In this paper, a high performance speed control approach using artificial neural networks (ANNs) and fuzzy logic for the field oriented induction motor (IM) is proposed. This control method is developed using model reference adaptive control (MRAC) to improve the performance of the IM speed. By using an adaptive neural network controller (ANNC) in the MRAC method, the speed of an IM can be controlled...
The low cost and high reliability of controlled induction motor drives without mechanical speed sensors made them to become more and more attractive. The information on the rotor speed is obtained from measured stator voltages and currents at the motor terminals with replace the sensor (mechanical sensor). Vector controlled drives require estimating the magnitude and spatial orientation of the fundamental...
This paper presents speed sensorless direct torque control (DTC) of induction motor using artificial intelligence (AI). The artificial neural network (ANN) MRAS-based speed estimation is used. The error between the reference model and the neural network based adaptive model is used to adjust the weights by on-line back propagation (BP) training algorithm. The speed loop regulation is carried out by...
In the paper a model reference adaptive sliding-mode control using on-line trained fuzzy neural network is applied to the sensorless induction motor drive system with MRAS type speed estimator. In this control structure adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller, in the direct field oriented control structure. Connective weights of this controller are trained...
The well-known direct torque control (DTC) is a very simple control method for inverter-fed AC drives, which characterized by fast dynamic response, structural simplicity, and low sensitivity to parameter changes. Attempts to combine DTC with SVM have led to new ways. This paper presents a new robust DTC-SVM for high performance induction machine drives. Simulation studies have been carried out for...
Sensorless field-oriented control of induction motors is widely used in high-performance applications. However, the decoupled control may be detuned due to the motor parameter variation and load torque disturbance. In this paper, a new fuzzy PI self-tuning robust speed controller with feedforward control of an adaptive disturbance observer is proposed for sensorless induction motor drives to ensure...
A.C motors, in general, have superior performance characteristics to their d.c. counterparts. However, despite these advantage a.c. motors lack the controllability and simplicity and so d.c. motors retain a competitive edge where precise control is required. As part of an overall project to develop an improved cycloconverter control strategy for induction motors. Simulation and modelling techniques...
The paper deals with two concepts of a model reference adaptive control (MRAC) of the induction motor drive with elastic joint. The adaptive speed controller uses fuzzy neural network equipped with additional option for on-line tuning its chosen parameters. In the paper PI-type and sliding-mode fuzzy logic controllers are used as the speed controllers, whose connective weights are trained on-line...
In this document a new proposal of speed vector control of induction motors based on robust adaptive VSC (variable structure control) law and its experimental validation are presented. This control scheme uses the SVPWM (space vector pulse width modulation) instead of the traditional current hysteresis comparator, because the space vector modulator eliminates the instability risk when the motor works...
A speed estimator based Model Reference Adaptive Fuzzy Control (MRAFC) principle is presented in this paper. In classical MRAC, the adaptive law is a fixed P-I gain and the estimated speed has larger overshoot in deceleration mode. So we propose a developed adaptive law based fuzzy logic controller, in which the adjusted output variables based fuzzy rule bases are added to the respective initial values...
In the paper a model reference adaptive control speed control (MRAC) using on-line trained fuzzy neural network (FNN) was applied to the sensorless induction motor drive system. In this control method fuzzy-logic controller is equipped with additional option for online tuning its chosen parameters. In the paper PI-type fuzzy logic controller is used as the speed controller, in the field oriented control...
This paper presents a modified method for estimating rotor speed of an indirect vector-controlled induction motor drive using fuzzy logic (FL) technique. The proposed method is based on model reference adaptive control that uses the stator current and rotor flux as state variables for estimating the speed. In this method, the stator current error is represented as a function of first degree of the...
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