scholarly journals An Adaptive Aeroelastic Control Approach using Non Linear Reduced Order Models

2014 ◽  
Author(s):  
Nikolaos D. Tantaroudas ◽  
Andrea Da Ronch ◽  
Guanqun Gai ◽  
Kenneth J. Badcock
Keyword(s):  
Reduced Order Models ◽  
Reduced Order ◽  
Control Approach ◽  
Non Linear

scholarly journals On the Potential of Reduced Order Models for Wind Farm Control: A Koopman Dynamic Mode Decomposition Approach

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6513
Author(s):  
Nassir Cassamo ◽  
Jan-Willem van Wingerden
Keyword(s):  
Wind Farm ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Reduced Order Models ◽  
Decomposition Approach ◽  
Reduced Order ◽  
Mode Decomposition ◽  
Non Linear ◽  
Farm Systems ◽  
Turbine Wake

The high dimensions and governing non-linear dynamics in wind farm systems make the design of numerical optimal controllers computationally expensive. A possible pathway to circumvent this challenge lies in finding reduced order models which can accurately embed the existing non-linearities. The work presented here applies the ideas motivated by non-linear dynamical systems theory—the Koopman Operator—to an innovative algorithm in the context of wind farm systems—Input Output Dynamic Mode Decomposition (IODMD)—to improve on the ability to model the aerodynamic interaction between wind turbines in a wind farm and uncover insights into the existing dynamics. It is shown that a reduced order linear state space model can reproduce the downstream turbine generator power dynamics and reconstruct the upstream turbine wake. It is further shown that the fit can be improved by judiciously choosing the Koopman observables used in the IODMD algorithm without jeopardizing the models ability to rebuild the turbine wake. The extensions to the IODMD algorithm provide an important step towards the design of linear reduced order models which can accurately reproduce the dynamics in a wind farm.

scholarly journals Numerical comparison of reduced order models for non-linear vibrations of damped plates

2012 ◽  
Author(s):  
F. Boumediene ◽  
L. Duigou ◽  
A. Miloudi ◽  
J.M. Cadou
Keyword(s):  
Harmonic Balance ◽  
Harmonic Balance Method ◽  
Computational Time ◽  
Numerical Comparison ◽  
Processing Unit ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Central Processing ◽  
Non Linear ◽  
Linear Vibrations

This work deals with the computation of the non-linear solutions of the vibration of damped plates by coupling a harmonic balance method and the asymptotic numerical method. These computations can lead to lengthy central processing unit (CPU) times if the solution sought contains an important number of harmonics. In this study, we propose two reduced order models which can be applied to solve this type of problem. Both reduced methods are based on a first computation carried out with a small number of harmonics (here two). Numerical examples of plate vibration show that these algorithms help save a great deal of computational time and can be applied to problems involving numerous harmonics.

Aeroelastic behaviour of a wing including geometric nonlinearities

2011 ◽  
Vol 115 (1174) ◽  
pp. 767-777 ◽  
Author(s):  
M. Y. Harmin ◽  
J. E. Cooper
Keyword(s):  
Aspect Ratio ◽  
Rational Fraction ◽  
Reduced Order Models ◽  
Structural Modelling ◽  
Geometric Nonlinearities ◽  
Reduced Order ◽  
Aerodynamic Model ◽  
Aeroelastic Model ◽  
Non Linear ◽  
Gust Response

Abstract A procedure for developing efficient aeroelastic reduced order models (ROMs) for aerospace structures containing geometric nonlinearities is described. The structural modelling is based upon a combined modal/FE approach that describes the non-linear stiffening effects from results of non-linear static analyses for a range of prescribed inputs. Once the structural ROM has been defined, it is coupled to the rational fraction approximation of the doublet lattice aerodynamic model corresponding to the wing planform. The aeroelastic model can then be used to predict the dynamic aeroelastic behaviour of the defined structure. The methodology is demonstrated on the aeroelastic model of a flexible high aspect ratio wing with the static deflections, LCO behaviour and gust response being predicted.

scholarly journals On the potential of reduced order models for wind farm control: a Koopman dynamic mode decomposition approach

2020 ◽  
Author(s):  
Nassir Cassamo ◽  
Jan-Willem van Wingerden
Keyword(s):  
Wind Farm ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Reduced Order Models ◽  
Decomposition Approach ◽  
Reduced Order ◽  
Mode Decomposition ◽  
Non Linear ◽  
Farm Systems ◽  
Turbine Wake

The high dimensions and governing non linear dynamics in wind farm systems make the design of numerical optimal controllers computationally expensive. A possible pathway to circumvent this challenge lies in finding reduced order models which can accurately embed the existing non linearities. The work here presented applies the ideas motivated by non linear dynamical systems theory - the Koopman Operator - to an innovative algorithm in the context of wind farm systems - Input Output Dynamic Mode Decomposition - to improve on the ability to model the aerodynamic interaction between wind turbines in a wind farm and uncover insights into the existing dynamics. It is shown that a reduced order linear state space model can reproduce the downstream turbine generator power dynamics and reconstruct the upstream turbine wake. It is further shown that the fit can be improved by judiciously choosing the Koopman observables used in the IODMD algorithm without jeopardizing the models ability to rebuild the turbine wake. The extensions to the IODMD algorithm provide an important step towards the design of linear reduced order models which can accurately reproduce the dynamics in a wind farm.

Sign in / Sign up

Export Citation Format

Share Document