Version 1
: Received: 19 September 2017 / Approved: 19 September 2017 / Online: 19 September 2017 (15:47:14 CEST)
How to cite:
Simani, S.; Castaldi, P. Robust Control Examples Applied to a Wind Turbine Simulated Model. Preprints2017, 2017090089. https://doi.org/10.20944/preprints201709.0089.v1
Simani, S.; Castaldi, P. Robust Control Examples Applied to a Wind Turbine Simulated Model. Preprints 2017, 2017090089. https://doi.org/10.20944/preprints201709.0089.v1
Simani, S.; Castaldi, P. Robust Control Examples Applied to a Wind Turbine Simulated Model. Preprints2017, 2017090089. https://doi.org/10.20944/preprints201709.0089.v1
APA Style
Simani, S., & Castaldi, P. (2017). Robust Control Examples Applied to a Wind Turbine Simulated Model. Preprints. https://doi.org/10.20944/preprints201709.0089.v1
Chicago/Turabian Style
Simani, S. and Paolo Castaldi. 2017 "Robust Control Examples Applied to a Wind Turbine Simulated Model" Preprints. https://doi.org/10.20944/preprints201709.0089.v1
Abstract
Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Experiments with the wind turbine simulator and the Monte–Carlo tools represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.
Keywords
Wind turbine simulator; data-driven and model-based approaches; fuzzy identification; on-line estimation; robustness and reliability
Subject
Engineering, Control and Systems Engineering
Copyright:
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.
