Robust Control Examples Applied to a Wind Turbine Simulated Model
AbstractWind 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 modeling and control become challenging problems. On the one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behavior. Therefore, the development of modeling 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 the development of robust control strategies when applied to a simulated wind turbine plant. Extended simulations with the wind turbine benchmark model and the Monte Carlo tool 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. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Simani, S.; Castaldi, P. Robust Control Examples Applied to a Wind Turbine Simulated Model. Appl. Sci. 2018, 8, 29.
Simani S, Castaldi P. Robust Control Examples Applied to a Wind Turbine Simulated Model. Applied Sciences. 2018; 8(1):29.Chicago/Turabian Style
Simani, Silvio; Castaldi, Paolo. 2018. "Robust Control Examples Applied to a Wind Turbine Simulated Model." Appl. Sci. 8, no. 1: 29.