Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows

Flow control has become a topic of great importance for several applications, ranging from commercial aircraft, to intercontinental pipes and skyscrapers. In these applications, and many more, the interaction with a fluid flow can have a significant influence on the performance of the system. In man...

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Main Author: Solis Cordova, Jose de Jesus
Other Authors: Coca, Daniel
Published: University of Sheffield 2017
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.703378
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spelling ndltd-bl.uk-oai-ethos.bl.uk-7033782017-10-04T03:44:04ZApplication of non-linear system identification approaches to modelling, analysis, and control of fluid flowsSolis Cordova, Jose de JesusCoca, Daniel2017Flow control has become a topic of great importance for several applications, ranging from commercial aircraft, to intercontinental pipes and skyscrapers. In these applications, and many more, the interaction with a fluid flow can have a significant influence on the performance of the system. In many cases the fluids encountered are turbulent and detrimental to the latter. Several attempts have been made to solve this problem. However, due to the non-linearity and infinite dimensionality of fluid flows and their governing equations, a complete understanding of turbulent behaviour and a feasible control approach has not been obtained. In this thesis, model reduction approaches that exploit non-linear system identification are applied using data obtained from numerical simulations of turbulent three-dimensional channel flow, and two-dimensional flow over the backward facing step. A multiple-input multiple-output model, consisting of 27 sub-structures, is obtained for the fluctuations of the velocity components of the channel flow. A single-input single-output model for fluctuations of the pressure coefficient, and two multiple-input single-output models for fluctuations of the velocity magnitude are obtained in flow over the BFS. A non-linear model predictive control strategy is designed using identified one- and multi-step ahead predictors, with the inclusion of integral action for robustness. The proposed control approach incorporates a non-linear model without the need for expensive non-linear optimizations. Finally, a frequency domain analysis of unmanipulated turbulent flow is perfumed using five systems. Higher order generalized frequency response functions (GFRF) are computed to study the non-linear energy transfer phenomena. A more detailed investigation is performed using the output FRF (OFRF), which can elucidate the contribution of the n-th order frequency response to the output frequency response.University of Sheffieldhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.703378http://etheses.whiterose.ac.uk/16303/Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
description Flow control has become a topic of great importance for several applications, ranging from commercial aircraft, to intercontinental pipes and skyscrapers. In these applications, and many more, the interaction with a fluid flow can have a significant influence on the performance of the system. In many cases the fluids encountered are turbulent and detrimental to the latter. Several attempts have been made to solve this problem. However, due to the non-linearity and infinite dimensionality of fluid flows and their governing equations, a complete understanding of turbulent behaviour and a feasible control approach has not been obtained. In this thesis, model reduction approaches that exploit non-linear system identification are applied using data obtained from numerical simulations of turbulent three-dimensional channel flow, and two-dimensional flow over the backward facing step. A multiple-input multiple-output model, consisting of 27 sub-structures, is obtained for the fluctuations of the velocity components of the channel flow. A single-input single-output model for fluctuations of the pressure coefficient, and two multiple-input single-output models for fluctuations of the velocity magnitude are obtained in flow over the BFS. A non-linear model predictive control strategy is designed using identified one- and multi-step ahead predictors, with the inclusion of integral action for robustness. The proposed control approach incorporates a non-linear model without the need for expensive non-linear optimizations. Finally, a frequency domain analysis of unmanipulated turbulent flow is perfumed using five systems. Higher order generalized frequency response functions (GFRF) are computed to study the non-linear energy transfer phenomena. A more detailed investigation is performed using the output FRF (OFRF), which can elucidate the contribution of the n-th order frequency response to the output frequency response.
author2 Coca, Daniel
author_facet Coca, Daniel
Solis Cordova, Jose de Jesus
author Solis Cordova, Jose de Jesus
spellingShingle Solis Cordova, Jose de Jesus
Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows
author_sort Solis Cordova, Jose de Jesus
title Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows
title_short Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows
title_full Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows
title_fullStr Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows
title_full_unstemmed Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows
title_sort application of non-linear system identification approaches to modelling, analysis, and control of fluid flows
publisher University of Sheffield
publishDate 2017
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.703378
work_keys_str_mv AT soliscordovajosedejesus applicationofnonlinearsystemidentificationapproachestomodellinganalysisandcontroloffluidflows
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