Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines

Abstract

(2014). Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines. Mechatronics, 24(8), 916-925. DOI: 10.1016/j.mechatronics.2014 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. a b s t r a c tManufacturing and maintenance costs arising out of wind turbine dynamic loading are one of the largest bottlenecks in the roll-out of wind energy. Individual Pitch Control (IPC) is being researched for cost reduction through load alleviation; it poses a challenging mechatronic problem due to its multi-input, multi-output (MIMO) nature and actuation constraints related to the wear of pitch bearings. To address these issues, Subspace Predictive Repetitive Control (SPRC), a novel repetitive control strategy based on the subspace identification paradigm, is presented. First, the Markov parameters of the system are identified online in a recursive manner. These parameters are used to build up the lifted matrices needed to predict the output over the next period. From these matrices an adaptive repetitive control law is derived.To account for actuator limitations, the known shape of wind-induced disturbances is exploited to perform repetitive control in a reduced-dimension basis function subspace. The SPRC methodology is implemented on a high-fidelity numerical aeroelastic environment for wind turbines. Load reductions are achieved similar to those obtained with classical IPC approaches, while considerably limiting the frequency content of the actuator signals.

Wind Tunnel Testing of Subspace Predictive Repetitive Control for Variable Pitch Wind Turbines

“…This is an extension of the methodology described in [24]: namely, to enable the algorithm to be tractable and realistic in real time in a wind turbine operating with a varying rotational period, controller synthesis and receding horizon implementation is done using rotor-position dependent basis functions. A new stability parameter is also proposed that describes the stability characteristics of the SPRC algorithm.…”

“…This LQ-like problem has also been formulated and solved in [24]; however, it has been noted that the size of state vector in this equation is very large (6P); and the solution is numerically complex to arrive at. In this specific case, to ensure that the problem can be solved recursively and online, the dimensionality is reduced by the following section.…”

“…Hence, the methodology of subspace predictive repetitive control (SPRC) was introduced in [24]. The SPRC approach combines RC with system identification for unknown dynamic systems that require periodic control, such as a wind turbine.…”

“…As compared with [24], where data-driven system identification and RC were implemented separately, this paper focuses on simultaneous system identification and control law update to establish and demonstrate the successful working of a stable, fully adaptive control methodology in a realistic wind tunnel experiment.…”

Iterative feedback tuning of wind turbine controllers

“…In the past decade, research has been conducted on developing load-reducing controllers that "learn" the optimal controller settings online Houtzager et al, 2013;Navalkar et al, 2014Xiao et al, 2016). These controllers are typically scheduled on basis functions and thereby mainly target the periodic wind turbine loading.…”