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Wind energy systems have been emerging as a highly significant solution to the problem of limited traditional energy sources. In this paper, control methodologies adapted to wind energy systems are topically reviewed. oHard computing or control techniques such as proportional-integral-derivative (PID), optimal, nonlinear, adaptive and robust and soft computing or control techniques such as neural...
The wide use of induction motors in high-precision drives calls for more advanced control architectures. Probably the greatest progress made in recent years is the field oriented control (FOC) which allowed the induction motor to move beyond the variable-speed control of Volts per Hertz drives. This work proposes the development of an adaptive neuro-fuzzy inference system (ANFIS) angular rotor speed...
This paper presents an dSPACE implementation of three-phase squirrel-cage induction motor control using direct torque control (DTFC) technique with the help of intelligent techniques. A fuzzy PI controller is used in the speed control loop. The classical lookup table is replaced by a neural network selector providing switching state to the inverter. The rotor speed is estimated by a simple open loop...
Due to its great potential value in theory and application, synthesized power and frequency control strategies of nonlinear wind power energy storage systems, especially combining with intelligent control methods, have been a focus in the academe. A synthesized power and frequency control method based on fuzzy neural networks presents nonlinear systems is proposed in this paper. The controller parameters...
A new algorithm for speed observer based on Model Reference Adaptive System (MRAS) is proposed for high performance induction motor drive. It uses stator current error based MRAS speed observer. The reference model of the stator current error based MRAS is the measured stator current components and the adaptive model is neuro-fuzzy based stator current observer. The adaptive model also needs the use...
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 following topics are dealt with: Web services; parallel genetic algorithm; nonlinear state observer design for 2-DOF twin rotor system using neural networks; digital image watermarking; performance evaluation and analysis of cluster based routing protocols in MANETs; microstrip bandpass filter; wireless body sensor mesh network; machine learning technique; word recognition; digital image compression;...
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...
In this paper, because the induction machines are described as the plants of highly nonlinear and parameters time-varying, in order to obtain a very well control performances that a conventional model reference adaptive inverse control (MRAIC) can not be gotten, a fuzzy neural network-based model reference adaptive inverse control strategy for induction motors is presented based on the rotor field...
In this paper, based on the radial basis function (RBF) neural network, a fuzzy predictive current control strategy for the doubly fed machine (DFM) is presented. The dynamic model of voltage, flux linkage, electromagnetic torque and mechanical motion equation for DFM are expressed. Because the DFM structure is complex and the DFM parameters are variable according to the operating conditions and environments,...
There are many torque ripples in traditional direct torque control (DTC) for permanent magnet synchronous motor(PMSM) drive, which are caused by the error of flux linkage estimation and hysteresis band amplitudes, etc.To solve these problems , a radial basis function (RBF) neural networks was designed to estimate the stator flux linkage, and fuzzy controller, in which zero-voltage vector is used,...
In this paper, speed controller based on artificial neural networks ANN and fuzzy logic controller FLC for vector control of AC motors is used. In the case using ANN controller, the tracking of the rotor speed is realized by adjusting the new weights of the network depending on the difference between the actual speed and the command speed. The controller is an adaptive and based on a nonlinear autoregressive...
Doubly-Fed Induction Generator (DFIG) has been widely used in Variable-Speed Constant-Frequency (VSCF) wind energy generation system. Vector control has already been applied to the DFIG control, which makes the DFIG gain good performance in the wind energy capturing operation. In recent years, many researches of vector control take the following manner to track the largest wind energy under the rated...
This paper presents design and implementation of a sensorless speed control with DTFC (direct torque and flux control) strategy for induction motor. The DTFC in its conventional form uses algorithms to select the components of the voltage inverter. This paper proposes to replace the conventional selector switches statements of the voltage inverter by a selector based on neural networks ANN (artificial...
The work describes an automatically online self-tunable fuzzy inference system (STFIS) of a new configuration of mini-flying called XSF (X4 stationary flyer) drone. A fuzzy controller based on online optimization of a zero order Takagi-Sugeno fuzzy inference system (FIS) by a back propagation-like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic...
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...
Pitch control by controlling the pitch angle of the wind wheel blade of the wind turbine generator can control the rotation speed when the wind turbine generator is starting and the output power when the wind turbine generator is on grid. The wind wheel can get maximum wind energy when its blade tip speed ratio is an optimum value. When wind speed is less than the rated speed, the rotation speed of...
This paper presents the intelligent control schemes for PM spherical stepper motor under the discrete stepping mode and continuous tracking mode. In the discrete stepping mode, a fuzzy inference system is used to predict the rotor orientation and perform the activation operation. Based on the non-linear system dynamic model under continuous trajectory tracking mode, the model reference adaptive control...
In this paper, a self-constructing recurrent fuzzy neural network (SCRFNN) method is proposed to control the speed of a permanent-magnet synchronous motor to track periodic reference trajectories. The proposed SCRFNN combines the merits of self-constructing fuzzy neural network (SCFNN) and the recurrent neural network (RNN). The structure learning is based on the partition of input space, and the...
In this paper, a novel predictive control algorithm based on T-S-FCMAC neural network is presented for three phase ACI motor control. On the basis of the principle of vector control, T-S-FCMAC neural network is adopted to build predictive model for motor speed and stator torque current, and predictive control algorithm is put forward to design the regulator with golden selection for motor speed. The...
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