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The current study proposed a robust sensor-less sliding mode second-order based on a super twisting algorithm (STA-SMSO) approach using a new observer Model Reference Adaptive System-Adaptative Neuro-Fuzzy Inference System (MRAS-ANFIS). This model was applied to a doubly fed induction generator (DFIG) wind turbine running under variable wind speed and DFIG fed with a power voltage source without a speed sensor, while the control objective was used to regulate independently, the active and reactive power DFIG stator were decoupled by using the field-oriented control technique. Additionally, this process reduced the cost of the control scheme and the size of DFIG by eliminating the speed sensor (encoder). In order to improve the traditional MRAS, the MRAS-ANFIS observer was proposed to replace the usual PI controller in the adaptation mechanism of MRAS with an Adaptative Neuro-Fuzzy Inference System (ANFIS) controller. The estimation of rotor position was tested and discussed under varying load conditions in low, zero, and high-speed region. The results mentioned that the proposed observer (MRAS-ANFIS) presented an attractive feature, such as guarantees finite time convergence, good response on speed wind variations, high robustness against machine parameter variations, and load variations compared to the conventional MRAS observer and MRAS-Fuzzy. Hence, the estimated rotor speed converged to their actual value has the capacity for estimating position in deferent region (low/zero/high) of speed. [ABSTRACT FROM AUTHOR]

The current study presents a robust sensorless control using passivity based control (PBC) combined with high gain observer (HGO). The proposed controller is applied to control the generated doubly-fed induction generator (DFIG) active and reactive power installed on a variable speed wind energy conversion system. The control objective is used to regulate independently the DFIG stator active and reactive power, which are decoupled by using the field oriented control technique. Additionally, this process leads to reduce the cost of control scheme by eliminating the speed sensor. Firstly, the DFIG is modeled under the port controlled Hamiltonian (PCH) model, as well as the method of simultaneous injection damping. Then, the DFIG is further modeled by assignment passivity based on the simultaneous injection damping and assignment (SIDA-PBC) control of the obtained model under such conditions and a comparison with the fuzzy sliding mode controller is carried out. Furthermore, the HGO is selected in order to estimate the rotor position and the speed from the measurement of the DFIG currents and voltages, and compared with fuzzy sliding mode observer. For testing the proposed control scheme performance, a 1.5 MW DFIG system is developed and simulated using MATLAB/Simulink. The obtained results demonstrate the effectiveness of the proposed control scheme in the presence of various DFIG parameters variation. Additionally, the control objective is achieved without speed sensor. [ABSTRACT FROM AUTHOR]

This paper proposes a H∞ Fuzzy robust controller for Doubly Fed Induction Generator (DFIG) based wind turbines. The power exchange between the machine stator and the grid is carried out by acting on the rotor via a bidirectional converter. The control objective is to regulate the stator active and reactive power generated from the DFIG by means of two kinds of controllers named H∞ PI and H∞ Fuzzy. Comparison study between the proposed controllers considering reference tracking and robustness to parameter variations is discussed. Simulation results illustrate the effectiveness of the H∞ Fuzzy controller compared with the other one for time-varying reference tracking and parameters variations, which improves quality and quantity of generated power. [ABSTRACT FROM AUTHOR]

In this study, a Sliding Mode (SM) methodology combined with a robust H∞ control scheme (SM-H∞) was proposed to control the stator active and reactive power generated by the Doubly Fed Induction Generator (DFIG). The purpose of the proposed controller is to improve the DFIG stator active and reactive power tracking performances by reducing chattering phenomena under variable wind speed, which provides major drawbacks of conventional SM controllers. The H∞ technique was used to define the SM attractive control part, which helps to reduce chattering phenomena and improves robustness in the presence of parameter variations and wind speed changing. The DFIG stator was directly connected to the grid and, its rotor was linked to the grid through a back-to-back converter. The proposed approach was tested using Matlab/Simulink and a comparison with the conventional SM and the SM fuzzy logic controllers was carried out. The results of simulation illustrated an effectiveness of the proposed SM-H∞ controller even in the presence of the DFIG parameter variations and speed changing compared with the other techniques. [ABSTRACT FROM AUTHOR]