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<p>I Australien är vattenresurserna begränsade. För lantbrukare är tillgängligheten på vatten mycket viktig. På grund av det torra klimatet kan inte de Australiensiska bönderna förlita sig på nederbörden. Bevattningssystemen är därför en viktig del i jordbrukningsindustrin.</p><p>Bevattningsområdet i Coleambally ligger i södra New South Wales nära gränsen till staten Victoria. Bevattningsnätet i Coleambally förser ofta bevattningskanalerna med för mycket vatten för att vara säker på att lantbrukarna får den mängd vatten de behöver. På grund av denna tillförsel av överskottvatten går stor mängd av vatten förlorad. Design av ett bättre reglersystem skulle kunna minska den stora förlusten av vatten.</p><p>En matematisk modell beskrivande dynamiken av bevattningssystemet är ett bra redskap vid en design av ett bättre reglersystem. Syftet med det här projektet var att genom systemidentifiering bygga en matematisk modell av bevattningssystemet. Modellen syftade till att beskriva vattennivån i en sträcka av bevattningskanalerna, sträckan i kanalen skulle ha två olika typer av luckor, en typ där vattnet strömmar över luckan och en annan typ där vattnet strömmar under luckan. En modell byggdes genom att parametrar från en vald modellstruktur estimerades från experimentella data. Data samlades under ett experiment som utfördes på en bevattningskanal i Coleambally.</p><p>Resultatet från systemidentifieringen blev en första ordningens output error grey box modell. Modellen visar goda resultat vid validering och bör kunna användas vid design av ett bättre reglersystem. Modellen visar så god överensstämmelse med valideringsdata att den även kan användas för olika fall av simulering.</p> / <p>Water resources in Australia are limited. For a farmer the access to water is crucial and due to the dry climate the farmers in Australia can not rely on precipitation. Irrigation is therefore a very important part of the farming industry.</p><p>The Coleambally Irrigation Area is situated in the southern parts of New South Wales close to the border of Victoria. The Irrigation Network often supplies the irrigation channels with too much water to be sure that the demand of water is satisfied. Due to this over supply a great amount of water gets wasted. Design of a bettercontrol system would be able to reduce the water wastage.</p><p>A mathematical model describing the dynamics of the irrigation system can be used as a tool for the control system design. The aim of this project was to build a mathematical model with the system identification approach. The model should be able to describe the downstream water level of a single pool of an irrigation channel which has both undershot and overshot gates. A model was built by estimating unknown parameters of a chosen model structure from a set of experimental data. The data was collected from an experiment performed on the real irrigation system in Coleambally.</p><p>The result of the system identification was a first order output error grey box model. The model performs well on validation data and may therefore be used for design of a more efficient control system. The model gave such good results that it additionally may be used for various simulation purposes.</p>

The contents of this thesis can be divided into two main parts. The first one is the development of an identification methodology for the modelling of complex industrial processes. The second one is the application of this methodology to the curl and twist problem. The main purpose behind the proposed methodology is to provide a schematic planning, together with some suggested tools, when confronted with the challenge of building a complex model of an industrial process. Particular attention has been placed to outlier detection and data analysis when building a model from old, or historical, process data. Another aspect carefully handled in the proposed methodology is the identifiability analysis. In fact, it is rather common in process modelling that the model structure turns out to be weakly identifiable. Consequently, the problem of variable selection is treated at length in this thesis, and a new algorithm for variable selection based on regularization has been proposed and compared with some of the classical methods, yielding promising results. The second part of the thesis is about the development of a curl predictor. Curl is the tendency of paper of assuming a curved shape and is observed mainly during humidity changes. Curl in paper and in paperboard is a long-standing problem because it may seriously affect the processing of the paper. Unfortunately, curl cannot be measured online, but only in the laboratory after that an entire tambour has been produced. The main goal of this project is then to develop a model for curl and twist, and eventually to implement it as an on-line predictor to be used by the operators and process engineers as a tool for decision/control. The approach we used to tackle this problem is based on grey-box modelling. The reasons for such an approach is that the physical process is very complex and nonlinear. The influence of some inputs is not entirely understood, and besides it depends on a number of unknown parameters and unmodelled/unmesurable disturbances. Simulations on real data show a good agreement with the measurement, particularly for MD and CD curl, and hence we believe that the model has an usable accuracy for being implemented as an on-line predictor. / QC 20100928

I Australien är vattenresurserna begränsade. För lantbrukare är tillgängligheten på vatten mycket viktig. På grund av det torra klimatet kan inte de Australiensiska bönderna förlita sig på nederbörden. Bevattningssystemen är därför en viktig del i jordbrukningsindustrin. Bevattningsområdet i Coleambally ligger i södra New South Wales nära gränsen till staten Victoria. Bevattningsnätet i Coleambally förser ofta bevattningskanalerna med för mycket vatten för att vara säker på att lantbrukarna får den mängd vatten de behöver. På grund av denna tillförsel av överskottvatten går stor mängd av vatten förlorad. Design av ett bättre reglersystem skulle kunna minska den stora förlusten av vatten. En matematisk modell beskrivande dynamiken av bevattningssystemet är ett bra redskap vid en design av ett bättre reglersystem. Syftet med det här projektet var att genom systemidentifiering bygga en matematisk modell av bevattningssystemet. Modellen syftade till att beskriva vattennivån i en sträcka av bevattningskanalerna, sträckan i kanalen skulle ha två olika typer av luckor, en typ där vattnet strömmar över luckan och en annan typ där vattnet strömmar under luckan. En modell byggdes genom att parametrar från en vald modellstruktur estimerades från experimentella data. Data samlades under ett experiment som utfördes på en bevattningskanal i Coleambally. Resultatet från systemidentifieringen blev en första ordningens output error grey box modell. Modellen visar goda resultat vid validering och bör kunna användas vid design av ett bättre reglersystem. Modellen visar så god överensstämmelse med valideringsdata att den även kan användas för olika fall av simulering. / Water resources in Australia are limited. For a farmer the access to water is crucial and due to the dry climate the farmers in Australia can not rely on precipitation. Irrigation is therefore a very important part of the farming industry. The Coleambally Irrigation Area is situated in the southern parts of New South Wales close to the border of Victoria. The Irrigation Network often supplies the irrigation channels with too much water to be sure that the demand of water is satisfied. Due to this over supply a great amount of water gets wasted. Design of a bettercontrol system would be able to reduce the water wastage. A mathematical model describing the dynamics of the irrigation system can be used as a tool for the control system design. The aim of this project was to build a mathematical model with the system identification approach. The model should be able to describe the downstream water level of a single pool of an irrigation channel which has both undershot and overshot gates. A model was built by estimating unknown parameters of a chosen model structure from a set of experimental data. The data was collected from an experiment performed on the real irrigation system in Coleambally. The result of the system identification was a first order output error grey box model. The model performs well on validation data and may therefore be used for design of a more efficient control system. The model gave such good results that it additionally may be used for various simulation purposes.

This thesis presents a grey-box model of the temperature and moisture content for each layer of the multi-ply paperboard inside the drying section of a paper mill. The distribution of the moisture inside the board is an important variable for the board quality, but is unfortunately not measured on-line. The main goal of this work is a model that predicts the moisture evolution during the drying, to be used by operators and process engineers as an estimation of the unmeasurable variables inside the drying section. Drying of carton board is a complex and nonlinear process. The physical phenomena are not entirely understood and the drying depends on a number of unknown parameters and unmodelled or unmeasurable features. The grey-box modelling approach, which consists in using the available measurements to estimate the unknown disturbances, is therefore a suitable approach for modelling the drying section. A major problem encountered with the modelling of the drying section is the lack of measurements to validate the model. Consequently, the correctness and uniqueness of the estimated variables and parameters are not guaranteed. We therefore carry out observability and identifiability analyses and the results suggest that the selected model structure is observable and identifiable under the assumption that specific measurements are available. Based on this analysis, static measurements in the drying section are carried out to identify the parameters of the model. The parameters are identified using one data set and the results are validated with other data sets. We finally simulate the model dynamics to investigate if predicting the final board properties on-line is feasible. Since only the final board temperature and moisture content are measured on-line, the variables and parameters are neither observable nor identifiable. We therefore regard the predictions as an approximation of the estimated variables. The semiphysical model is complemented with a nonlinear Kalman filter to estimate the unmeasured inputs and the unmodelled disturbances. Data simulations show a good prediction of the final board temperature and moisture content at the end of the drying section. The model could therefore possibly be used by operators and process engineers as an indicator of the board temperature and moisture inside the drying section. / QC 20101112

<p>This thesis presents a grey-box model of the temperature and moisture content for each layer of the multi-ply paperboard inside the drying section of a paper mill. The distribution of the moisture inside the board is an important variable for the board quality, but is unfortunately not measured on-line. The main goal of this work is a model that predicts the moisture evolution during the drying, to be used by operators and process engineers as an estimation of the unmeasurable variables inside the drying section.</p><p>Drying of carton board is a complex and nonlinear process. The physical phenomena are not entirely understood and the drying depends on a number of unknown parameters and unmodelled or unmeasurable features. The grey-box modelling approach, which consists in using the available measurements to estimate the unknown disturbances, is therefore a suitable approach for modelling the drying section.</p><p>A major problem encountered with the modelling of the drying section is the lack of measurements to validate the model. Consequently, the correctness and uniqueness of the estimated variables and parameters are not guaranteed. We therefore carry out observability and identifiability analyses and the results suggest that the selected model structure is observable and identifiable under the assumption that specific measurements are available. Based on this analysis, static measurements in the drying section are carried out to identify the parameters of the model. The parameters are identified using one data set and the results are validated with other data sets.</p><p>We finally simulate the model dynamics to investigate if predicting the final board properties on-line is feasible. Since only the final board temperature and moisture content are measured on-line, the variables and parameters are neither observable nor identifiable. We therefore regard the predictions as an approximation of the estimated variables. The semiphysical model is complemented with a nonlinear Kalman filter to estimate the unmeasured inputs and the unmodelled disturbances. Data simulations show a good prediction of the final board temperature and moisture content at the end of the drying section. The model could therefore possibly be used by operators and process engineers as an indicator of the board temperature and moisture inside the drying section.</p>

This research aims to explore new ways of assessing energy performance within housing units. The mainobjective of this work is to propose a heat dynamics model based on monitoring data, to contribute towardsan energy-efficient transition in the building sector. An extensive study on the available mathematical and statistical tools is described in order to determine aholistic solution, found in grey-box models. This model approach offers the possibility of understandingmultivariate systems, which can be applied to a housing-unit heat flow dynamics. Through the iterative process of testing each possible model, this work determines the one with bestexplanatory power, defining the thermal characteristics of the studied housing unit. This method allows thedetection of underperforming dwellings among constructions with high energy-efficiency standards. This investigation reflects the feasibility of employing grey-box models to predict the dynamics of heatrelated systems. Moreover, it sets the basis for new ways of employing the monitoring data of dwellings. / Denna forskning syftar till att utforska nya sätt att bedöma energiprestanda inom bostäder. Huvudsyftetmed detta arbete är att föreslå en värmedynamikmodell baserad på övervakningsdata för att bidra till enenergieffektiv övergång inom byggsektorn. En omfattande studie av tillgängliga matematiska och statistiska verktyg beskrivs för att bestämma enhelhetslösning, som finns i gråboxmodeller. Denna modellstrategi ger möjlighet att förstå multivariatasystem, som kan tillämpas på en hushålls värmedynamik. Genom den iterativa processen att testa varje möjlig modell bestämmer detta arbete den med bästförklarande kraft, och definierar de studerade husenhetens termiska egenskaper. Denna metod gör detmöjligt att upptäcka underpresterande bostäder bland anläggningar med hög energieffektivitetsstandard. Denna undersökning återspeglar möjligheten att använda gråboxmodeller för att förutsäga dynamiken ivärmerelaterade system. Dessutom lägger den grunden för nya sätt att använda övervakningsdata förbostäder.

Kohlenstofffasern sind aufgrund ihrer hohen massespezifischen mechanischen Belastbarkeit ein unverzichtbarer Werkstoff im Leichtbau. Diese werden mittels eines zeitaufwendigen, thermooxidativen Stabilisierungs- und eines inerten Carbonisierungsprozesses hergestellt. Bedingt durch die kommerziell dominierte Forschung basiert der Großteil der veröffentlichten Optimierungsansätze für diese Prozessschritte bis heute auf unvollständigen, empirischen oder nicht-parametrischen, datengetriebenen Modellen. In der vorliegenden Arbeit werden hybride semi-parametrische Ansätze unter Berücksichtigung der Eigenschaften des Precursorsystems und der Prozessparameter für die Modellierung des Stabilisierungsprozesses untersucht. / Carbon fibers are an indispensable material in lightweight construction due to their mass-specific mechanical load capaci-ty. These are produced by means of a time-consuming, thermo-oxidative stabilization process and an inert carbonizationprocess. Due to commercially dominated research, the majority of published optimization approaches for these processsteps to date is based on incomplete, empirical or non-parametric, data-driven models. In the present work, hybrid semi-parametric approaches considering the properties of the precursor system and the process parameters are investigated formodeling of the stabilization process.

Nombreux sont les problèmes classiquement rencontrés dans les sciences de l'ingénieur dont la résolution fait appel à l'estimation d'état d'un système par le biais d'un observateur. La synthèse d'un observateur n'est envisageable qu'à la condition de disposer d'un modèle à la fois exploitable et représentatif du comportement dynamique du système. Or, la modélisation du système et la synthèse de l'observateur deviennent des tâches difficiles à accomplir dès lors que le comportement dynamique du système doit être représenté par un modèle de nature non linéaire. Face à ces difficultés, l'approche multimodèle peut être mise à profit. Les travaux présentés dans cette thèse portent sur les problèmes soulevés par l'identification, l'estimation d'état et le diagnostic de systèmes non linéaires représentés à l'aide d'un multimodèle découplé. Ce dernier, composé de sous-modèles qui peuvent être de dimensions différentes, est doté d'un haut degré de généralité et de flexibilité et s'adapte particulièrement bien à la modélisation des systèmes complexes à structure variable. Cette caractéristique le démarque des approches multimodèles plus conventionnelles qui ont recours à des sous-modèles de même dimension. Après une brève introduction à l'approche multimodèle, le problème de l'estimation paramétrique du multimodèle découplé est abordé. Puis sont présentés des algorithmes de synthèse d'observateurs d'état robustes vis-à-vis des perturbations, des incertitudes paramétriques et des entrées inconnues affectant le système. Ces algorithmes sont élaborés à partir de trois types d'observateurs dits à gain proportionnel, à gain proportionnel-intégral et à gain multi-intégral. Enfin, les différentes phases d'identification, de synthèse d'observateurs et de génération d'indicateurs de défauts sont illustrées au moyen d'un exemple académique de diagnostic du fonctionnement d'un bioréacteur / The state estimation of a system, with the help of an observer, is largely used in many practical situations in order to cope with many classic problems arising in control engineering. The observer design needs an exploitable model able to give an accurate description of the dynamic behaviour of the system. However, system modelling and observer design can not easily be accomplished when the dynamic behaviour of the system must be described by non linear models. The multiple model approach can be used to tackle these difficulties. This thesis deals with black box modelling, state estimation and fault diagnosis of nonlinear systems represented by a decoupled multiple model. This kind of multiple model provides a high degree of generality and flexibility in the modelling stage. Indeed, the decoupled multiple model is composed of submodels which dimensions can be different. Thus, this feature is a significant difference between the decoupled multiple model and the classical used multiple model where all the submodels have the same dimension. After a brief introduction to the multiple model approach, the parametric identification problem of a decoupled multiple model is explored. Algorithms for robust observers synthesis with respect to perturbations, modelling uncertainties and unknown inputs are afterwards presented. These algorithms are based on three kinds of observers called proportional, proportional-integral and multiple-integral. Lastly, identification, observers synthesis and fault sensitivity signals generation are illustrated via a simulation example of a bioreactor

A significant challenge with permanent magnet synchronous motors (PMSMs) is thermal management. Thermal stress can lead to irreversible damage to components, and to enable efficient cooling, a thermal model is needed. In this thesis paper, methods for estimating the hot spot temperature of the windings in PMSMs used in heavy-duty EVs are investigated. The methods include black-box models and lumped parameter thermal network-based models. The results reveal that the implemented models are not sufficient for achieving the desired accuracy, and indicate that more parts of the windings need to be considered.