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Shock and Vibration
Volume 2018, Article ID 5737359, 12 pages
https://doi.org/10.1155/2018/5737359
Research Article

Vibration Control of Wind Turbine Blade Based on Data Fitting and Pole Placement with Minimum-Order Observer

College of Mechanical & Electronic Engineering, Shandong University of Science & Technology, Qingdao 266590, China

Correspondence should be addressed to Tingrui Liu; moc.361@9999iurgnituil

Received 26 September 2017; Accepted 1 April 2018; Published 24 May 2018

Academic Editor: Marc Thomas

Copyright © 2018 Tingrui Liu and Lin Chang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Vibration control of wind turbine blade with minimum control cost is investigated. Realization of minimum control cost is based on pole placement with minimum-order observer (PPMO). The blade analysis employs a novel compromise method between the 2D airfoil analysis method and the 3D coupled blade body analysis method based on data fitting. It not only ensures certain accuracy, but also greatly improves the speed of calculation. The Wilson method, developed on the basis of the blade momentum theory, is adopted to optimize the structural parameters of the blade, with all parameters fitted as general model Sin6 (Sum of Sine) fitting curves. Also the aerodynamic coefficients based on data obtained by Xfoil software are fitted. Pole placement technology based on minimum-order observer is applied to control unstable vibrations of vertical bending and lateral bending with minimum control cost characterized by the energy consumption of the controller. The pole placement technology is a novel pole assignment technique based on self-poles derived from constant stable eigenvalues, which can effectively avoid the mismatch problems caused by pole selection. The superiority of PPMO can be apparently demonstrated by comparison of linear quadratic regulator (LQR). Analytical proof of the control accuracy and feasibility analysis of the physical realization of the PPMO algorithm are also investigated by experimental platform of hardware-in-the-loop simulation.