Wind turbine multivariable optimal control based on incremental state model

Adánez García-Villaraco, José Miguel, Al-Hadithi, Basil M. and Jiménez Avello, Agustín ORCID: https://orcid.org/0000-0003-4918-5918 (2018). Wind turbine multivariable optimal control based on incremental state model. "Asian Journal of Control", v. 20 (n. 6); pp. 2075-2087. ISSN 1934-6093. https://doi.org/10.1002/asjc.1720.

Description

Title: Wind turbine multivariable optimal control based on incremental state model
Author/s:
Item Type: Article
Título de Revista/Publicación: Asian Journal of Control
Date: November 2018
ISSN: 1934-6093
Volume: 20
Subjects:
Freetext Keywords: Incremental state model; Multivariable systems; Optimal control; Wind turbine
Faculty: Centro de Automática y Robótica (CAR) UPM-CSIC
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The multivariable optimal control of a wind turbine by an approach based on incremental state model is proposed. The advantages of incremental state model in comparison with the non incremental one are that the control action cancels steady state errors and incremental state solves the problem of computing the target state, choosing zero as an objective. Linear Quadratic Regulator (LQR) and optimal state observer are applied. The effectiveness of the proposed control method, over the non incremental one, is examined by applying the linear controllers to the nonlinear wind turbine model. The results show that incremental LQR control presents good transient response and zero steady state errors, even in presence of disturbances, nonlinearities and modelling errors.

Funding Projects

Type
Code
Acronym
Leader
Title
Government of Spain
DPI2014‐53525‐C3‐1‐R
NAVEGASE
Unspecified
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More information

Item ID: 55413
DC Identifier: https://oa.upm.es/55413/
OAI Identifier: oai:oa.upm.es:55413
DOI: 10.1002/asjc.1720
Official URL: https://onlinelibrary.wiley.com/doi/full/10.1002/a...
Deposited by: Memoria Investigacion
Deposited on: 13 Jun 2019 07:40
Last Modified: 30 Nov 2019 23:30
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