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This paper presents a novel design and an application of an adaptive neuro-fuzzy controller technique with a linearized induction motor control scheme for the better dynamic performance of induction motor drive control. The linear decoupling of rotor flux and torque of induction motor is carried out by modelling and simulating the induction motor in stationary reference frame with feedback controller...
This paper presents an adaptive neuro-fuzzy inference system (ANFIS) based speed control for indirect field oriented controlled induction motor drive. The obtaining of maximum torque and efficiency in the motor necessitates a successful nonlinear speed control method due to the non-linear structure of the system. In this work, a fuzzy logic controller (FLC) and ANFIS controller has been developed...
This paper presents a comparative study between a self-tuning fuzzy (STF) PID controller, Fuzzy Logic Controller and conventional PID controller based speed control system for a current source PWM inverter fed indirect field oriented control of Induction Motor (IM) Drives. In this work the conventional PI controller is replaced by self-tuning fuzzy PID based intelligent controller. The fuzzy logic...
In this research study, a new speed control scheme is proposed for direct torque and flux control (DTFC) of induction motor drive (IMD) to replace the conventional constant gain PI-speed controller (PISC). The conventional PISC offers poor dynamic response of stator current, torque and motor speed under sudden change in speed or load torque disturbances. In order to improve the dynamic as well as...
Efficiency improvement of motor drives is important not only from the viewpoints of energy loss and hence cost saving, but also from the perspective of environmental pollution. Several efficiency optimization methods for induction motor (IM) drives have been introduced nowadays by researchers. Distinctively, artificial intelligence (AI)-based techniques, in particular Fuzzy Logic (FL) one, have been...
The paper presents a fuzzy logic speed control system based on fuzzy logic approach for an indirect vector controlled induction motor drive for high performance. The analysis, design and simulation of the fuzzy logic controller for indirect vector control induction motor are carried out based on fuzzy set theory. The proposed fuzzy controller is compared with PI controller with no load and various...
Because of the low maintenance and robustness induction motors have many applications in the industries. Most of these applications need fast and smart speed control system. This paper introduces a smart speed control system for induction motor using fuzzy logic controller. Induction motor is modeled in synchronous reference frame in terms of dq form. The speed control of induction motor is the main...
This paper presents a sensorless speed observer method of an induction motor using an artificial intelligent technique in field-oriented control system. Speed and rotor flux are estimated from only measurable variables, the stator voltages and currents. The proposed estimation algorithm uses a deterministic state observer combined with an intelligent adaptive mechanism based on fuzzy logic, and using...
In this paper, a robust self-tuning fuzzy speed controller for direct torque control using space vector modulation (SVM) technique is proposed for the high performance drives of induction motor. The design of robust self-tuning fuzzy speed controller greatly affects the performance of Induction Motor (IM) fed with a Voltage Source Inverter (VSI). The performance of the proposed self-tuning Fuzzy PI...
Because of its low maintenance and robustness, induction motors have many applications in the industries. Most of these applications need fast and smart speed control system. This paper introduces a smart speed control system for induction motor using fuzzy logic controller. Induction motor is modeled in synchronous reference frame in terms of dq form. The speed control of induction motor is the main...
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...
The present work is a contribution to improve efficiency and the robustness of a indirect field oriented of induction motor drives. The efficiency of the motor deteriorates for two reasons: The variation of rotor resistance and operation under light loads, with a constant field. For these reasons, a method is proposed to choose the optimal field to minimize total machine losses. On the other hand,...
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 field orientation control of an induction motor has been permitted fast transient response by decoupled torque and flux. The conventional PI controller has been widely used in industrial application due to the simple control algorithm and easy implementation. With help of the Matlab/Simulink, block model of an induction motor drives can be constructed. This paper presents a novel fuzzy controller...
A sensorless direct torque controlled (DTC) induction motor drive fed by a 3-level inverter is presented based on discrete space vector modulation. A novel vector synthesis sequence is proposed to solve the problems caused by the topology of the 3-level inverter, such as neutral point unbalance and excessive voltage jump, while maintaining the merits of simplicity and robustness. Fuzzy logic control...
The application of three phase squirrel cage induction motor as an industrial drive is a common practice. With passage of time these industrial motors are subjected to incipient faults which if undetected can lead to a major fault. Recently artificial neural network, fuzzy logic and genetic algorithm have been employed to assist the diagnosis task and to interpret the data for machine condition. In...
Vector control of induction motor is an efficient approach to control the speed of induction motor used for industrial drives. Although the vector control is very popular method but there lies difficulty in obtaining an accurate model of induction motor (IM) owing to the variation of induction motor parameters, such as resistance, inductance and time constant. Therefore, to cope up with this uncertainty...
This paper implements a new observer model in parallel with a sliding mode concept for a field oriented control drive system. The proposed system accounts for the problem of stator resistance variation. The use of feedback correction on the output of the observer eliminates the effect of stator resistance and makes the new observer robust in terms of motor parameter variation. A comparison between...
This paper proposes a new indirect adaptive fuzzy controller based on interval type-2 fuzzy logic systems for indirect vector controlled induction motor drive. Type-2 fuzzy controller compared with type-1 fuzzy controller, has the advantage that it can take into account the linguistic uncertainties present in the rules of the estimated models. The proposed control scheme consists of a combination...
In this paper efficiency optimization approaches based on fuzzy logic and genetic algorithms (GAs) are proposed. An improvement of efficiency is obtained by adjusting the magnetizing current component with respect to the torque current component to give the minimum total copper and iron losses. Some simulation results are given and compared with those obtained by using fuzzy logic and classical vector...
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