pitch control
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A few studies have been conducted recently in order to improve the aerodynamic performance of Darrieus vertical-axis wind turbines with straight blades (H-type VAWTs). The blade pitch angle control is proposed to enhance the performance of H-type VAWTs. This paper aims to investigate the performance of an H-type VAWT in terms of its power output and self-starting capability using an intelligent blade pitch control strategy based on a multi-layer perceptron artificial neural network (MLP-ANN) method. The performance of the proposed blade pitch controller is investigated by adding a conventional controller (PID) to the MLP-ANN controller (i.e., a hybrid controller). The dynamics of an H-type VAWT is mathematically modeled in a nonlinear state space for the stability analysis in the sense of Lyapunov. The effectiveness of the proposed pitch control system is validated by building an H-type VAWT prototype model that is extensively tested outdoors under different conditions for both fixed and variable pitch angle configurations. Results demonstrated that the blade-pitching technique enhanced the power output of an H-type VAWT by approximately 22%. The hybrid controller that used a high percentage of the MLP-ANN controller achieved a better control performance by reducing the overshoot of the control response at high rotor speeds.

In this article, we propose a recent iterative learning algorithm for sensor data fusion to detect pitch actuator failures in wind turbines. The development of this proposed approach is based on iterative learning control and Lyapunov’s theories. Numerical experiments were carried out to support our main contribution. These experiments consist of using a well-known wind turbine hydraulic pitch actuator model with some common faults, such as high oil content in the air, hydraulic leaks, and pump wear.

Modern multi-megawatt wind turbines are currently designed as pitch-regulated machines, i.e., machines that use the rotation of the blades (pitching) in order to adjust the aerodynamic torque, such that the power is maintained constantly throughout a wide range of wind speeds when they exceed the design value (rated wind speed). Thus, pitch control is essential for optimal performance. However, the pitching activity is not for free. It introduces vibrations to the tower and blades and generates fatigue loads. Hence, pitch control requires a compromise between wind turbine performance and safety. In the past two decades, many approaches have been proposed to achieve different objectives and to overcome the problems of a wind energy converter using pitch control. The present work summarizes control strategies for problem of wind turbines, which are solved by using different approaches of pitch control. The emphasis is placed on the bibliographic information, but the merits and demerits of the approaches are also included in the presentation of the topics. Finally, very large wind turbines have to simultaneously satisfy several control objectives. Thus, approaches like collective and individual pitch control, tower and blade damping control, and pitch actuator control must coexist in an integrated control system.

This paper exhibits a comparative assessmentbased on time response specification performance between modern and classical controller for a pitch control system of an aircraft system. The dynamic modeling of pitch control system is considered on the design of an autopilot that controls the pitch angle It starts with a derivation of a suitable mathematical model to describe the dynamics of an aircraft. For getting close to actual conditionsthe white noise disturbance is applied to the system.In this paper it is assumed that the modelpitch control systemis not available. So using the identification system and Box-Jenkins model estimator we identify the pitch control system System’s identification is a procedure for accurately characterizing the dynamic response behavior of a complete aircraft, of a subsystem, or of an individual component from measureddata.To study the effectiveness of the controllers, the LQR Controller and PID Controller and fuzzy controller is developed for controlling the pitch angle of an aircraft system. Simulation results for the response of pitch controller are presented instep’s response. Finally, the performances of pitch control systems are investigated and analyzed based on common criteria of step’s response in order to identify which control strategy delivers better performance with respect to the desired pitch angle. It is found from simulation, that the fuzzy controller gives the best performance compared to PID and LQR controller.

Abstract It has been well established that non-torque main shaft loads influence the internal drive train loads. This paper proposes a scheme that compensates for non-torque loads in the blade pitch controller. The compensation scheme is implemented on a dynamic model developed in FAST/Simulink. Three wind conditions of 8, 11.4 and 20 m/s are examined. The dynamic analysis of the bending moment in the low-speed shaft showed a reduction in bending moment by 3 % for the rated wind speed (11.4 m/s) and 1.8 % for the above-rated wind speed (20 m/s), highlighting the effectiveness of the proposed scheme. However, a reduction in bending moment also slightly decreased the shaft’s speed by 2.3 % and 0.5 %, respectively. Similarly, the turbine power was decreased by 9 % and 1 %, respectively. In comparison, further gain scheduling within the compensation scheme reduces the power loss to as low as 0.3 %. The 2 to 3 % reduction in the low-speed shaft bending moment can significantly influence the drive train loads and easily outweigh any loss resulting in the shaft rotational speed and turbine power. Thus, this paper shows that using bending moment error as feedback within the compensation scheme positively affects the low-speed shaft’s bending moment with the eventual potential of reducing drivetrain loads.