Neste trabalho, é apresentado um estudo sobre um sistema de micro geração de energia a partir da vibração de uma viga em balanço utilizando um transdutor piezoelétrico. A análise é feita levando-se em consideração as dimensões da viga utilizada, tipo de gerador piezoelétrico e diferentes tipos de cargas acopladas a este. O sistema de geração tem sua excitação realizada por um atuador piezoelétrico, que é alimentado por uma fonte de tensão com amplitude, frequência e forma de onda ajustáveis. A avaliação da potência de saída e influência dos diferentes tipos de carga acoplados a saída são analisados. As cargas utilizadas são: puramente resistiva, resistiva-capacitiva e não linear, por meio de um retificador de onda completa. Para avaliar experimentalmente os resultados analíticos foi utilizado um protótipo de uma viga em balanço construída com uma barra de alumínio exposta a uma excitação, induzida por um outro transdutor piezoelétrico ligado a uma placa dSpace controlada por um computador. Os parâmetros do sistema são identificados sendo possível determinar sua influência na saída e realizando assim uma análise pontual do micro gerador piezoelétrico quando submetido a uma carga qualquer. Os resultados da geração com os diferentes tipos de cargas são comparados, bem como a influência destas na dinâmica do sistema. As potências máximas são apresentadas em diferentes modos de vibração depois de otimizadas. Foram obtidos os seguintes resultados: 3;357mW com uma resistência de 200k no primeiro modo; 13;17mW com uma resistência de 50k no segundo modo; para o terceiro e quarto modos de vibração a máxima potência é obtida com a resistência de 10k, sendo 10;22mW e 15;63mW, respectivamente. A alteração da frequência de vibração é de aproximadamente 0;2% para os modos de vibração em função da resistência máxima e mínima. Para a carga resistiva-capacitiva, o comportamento da geração não é afetado significativamente para os valores de resistência de 1M e 100k. Com os valores de 10k e 1k a potência ativa se eleva em 30%, aproximadamente. O comportamento da carga não linear é aproximado por uma impedância com característica capacitiva. Sendo que, com a elevação da frequência, a impedância vista pelo gerador piezoelétrico é diminuída. A energia armazenada é de 0;8039mJ, 2;5245mJ e 1;3041mJ para o primeiro, segundo e terceiro modos de vibração, respectivamente. / This work presents a study of a energy harvesting system based on vibration from a cantilever beam utilizing a piezoelectric generator. The analysis considers the dimensions of the beam, type of piezoelectric generator and di erent types of loads coupled. A piezoelectric actuator is handles for the system excitement, powered by a voltage source with adjustable amplitude, frequency and shape. Are evaluate the output power and the in uence of di erent charge types coupled to the piezoelectric generator. The loads are purely resistive, resistive-capacitive and non-linear, by a full-wave bridge recti er. To check experimentally the analytical results, are used a prototype of a cantilever beam constructed with an aluminum bar exposed to an excitation induced by another piezoelectric transducer attached to a dSpace board controlled by a computer. The system parameters are individually identi ed to determine their in uence on output, allowing the punctual analysis of the piezoelectric harvesting when subjected to any load. The results of power generation are compare with di erent types of loads as well as its in uence on the dynamic of the system. After a optimization, the greatest power delivered to the load happen in di erent vibrational modes. We obtain the following results: 3:357mW with a 200k resistance in the rst mode; 13:17mW with a 50k resistance in the second mode, for the third and fourth vibration modes greatest power is obtained with the 10k resistance, being 10:22mW and 15:63mW, respectively. The modi cation of the vibration frequency are approximately 0:2% for all vibration modes depending on the largest and smallest resistance. For the resistive-capacitive load, the generation behavior are not a ect to the 1M and 100k resistance. With the 10k and 1k values, the active power increases by approximately 30%. The nonlinear load behavior are approach by an impedance with capacitive characteristics. With increasing of frequency, the impedance seen by the piezoelectric harvester is decreased. The energy stored is 0:8039mJ, 2:5245mJ and 1:3041mJ for the rst, second and third vibration modes, respectively.

The recently-developed simultaneous solution scheme for solving nonlinear rotordynamic systems running on foil-air bearings (FABs) has overcome the practice of decoupling the air film, foil and rotor equations that has been typically followed to reduce computational burden at the expense of accuracy. However, the published works using the simultaneous solution technique have been limited to a simple bump foil model in which the individual bumps were modelled as independent spring-damper (ISD) subsystems. The overall aim of this thesis is to present methods that enable more realistic FAB models to be integrated into the simultaneous solution scheme, without compromising its efficiency. Two such alternative approaches are presented: (1) the full foil structure modal model (FFSMM) of the bump foil structure; (2) non-parametric system identification of the entire FAB i.e. foil and air film. The FFSMM provides a more realistic model of the bump foil structure since it considers the interaction between the bumps and foil inertia. Although the foil damping is still assumed to be linear, the model presented is adaptable to nonlinear friction forces. The dynamics of the bump foil structure are studied by finite element methods and experimentally validated using a purpose-made corrugated foil structure. The FE result shows that the effect of bump interaction increases the effective stiffness of the FAB. Foil inertia is not important for the range of speeds considered in the thesis, but the experimentally validated fundamental foil resonance of around 2 kHz is within the operating speed range of high-speed turbomachinery. The FFSMM can take into account the curvature of the bearing sleeve, but the effect of this feature is proven to be negligible for the size of bearing used in the study. The FFSMM simulation results are correlated against ISD model results and published experimental maximum film thickness and locus of the journal response. The results of the FFSMM were then compared against experimental results under unbalance response conditions measured from a purpose-built test rig. The rotor was mathematically modelled using rigid body equations of motion, which were validated by modal analysis. The unbalance rotor response results obtained from the FFSMM and experiment both show that the sub-synchronous motion is not only mainly influenced by the increment of unbalance mass, but, to a greater extent, the increment of rotor speed. The findings show good agreement between the model and experimental results. This thesis also presents the non-parametric system identification of a FAB, which is also adaptable to the simultaneous solution scheme. This work is motivated by two advantages: (a) it removes computational limitations by replacing the whole bearing equations by a displacement/force relationship, where the air film effect is taken into account; (b) it can capture complications that cannot be easily modelled, if the identification is based on empirical data. A Recurrent Neural Network (RNN) is trained to identify the full numerical model of a FAB over a wide range of speeds. The identified model of the FAB is adapted into the frequency domain rotor-dynamic simultaneous solution technique by using harmonic balance (HB) methods, thus directly producing the steady-state orbit response. Excellent correlation is demonstrated between the identification technique and the full numerical model under two validation processes: (i) using different sets of input/output data; (ii) the application of the identified RNN-FAB model to HB analysis in lieu of the full numerical model of the FAB.

O método de identificação por minimização do erro de predição está relacionado com um problema de otimização não convexo. É comum utilizar algoritmos iterativos para resolver o problema de otimização. Contudo, os algoritmos iterativos podem ficar presos em mínimos locais da função custo ou convergir para a borda do domínio de busca. Uma análise da função custo e condições suficientes para garantir a convergência dos algoritmos iterativos para o mínimo global são apresentadas neste trabalho. Observa-se que estas condições dependem do espectro do sinal de entrada utilizado no experimento. Este trabalho apresenta ferramentas para melhorar a convergência dos algoritmos para o mínimo global, as quais são baseadas na manipulação do espectro do sinal de entrada. / The Prediction Error Method is related to a non-convex optimization problem. It is usual to apply iterative algorithms to solve this optimization problem. However, iterative algorithms can get stuck at a local minimum of the cost function or converge to the border of the searching space. An analysis of the cost function and sufficient conditions to ensure the convergence of the iterative algorithms to the global minimum are presented in this work. It is observed that this conditions depend on the spectrum of the input signal used in the experiment. This work presents tools to improve the convergence of the algorithms to the global minimum, which are based on the manipulation of the input spectrum.

Na modelagem caixa branca obtém-se um modelo para um processo a partir do equacionamento dos fenômenos físicos/químicos envolvidos. Estes modelos são para- metrizados, mas os valores dos parâmetros utilizados muitas vezes são desconhecidos. Nestes casos ´e necessário efetuar um procedimento de identificação paramétrica o que representa um problema altamente desafiador, com muitas questões teóricas e práticas em aberto, quando os parâmetros aparecem de forma n˜ao linear no modelo. O objetivo deste trabalho ´e apresentar e estudar um método capaz de determinar se uma estrutura de modelo predeterminada pode ser identificada e que possa ser utilizado em conjunto com algum outro método de identificação, para identificar o sistema. O método que será apresentado é baseado em álgebra diferencial e é conhecido como algoritmo de Ritt. O algoritmo de Ritt transforma uma estrutura de modelo polinomial predeterminada em regressões lineares nos parâmetros a partir das quais pode-se utilizar os métodos dos mínimos quadrados ou variáveis instrumentais para identificar o sistema. Apresentaremos alguns estudos de caso e faremos a análise de identificabilidade para cada um deles. Em alguns casos identificaremos o sistema e estudaremos a consistência e precisão das estimativas. / In white box modeling we obtain a model for a process from the equations of the physical/chimical phenomena involved. These models are parameterized, but the parameters used are often unknown. In these cases it is necessary to perform a parametric identification procedure which represents a highly challenging problem, with many theoretical and practical open questions when the parameters are non- linears in the model. The aim of this work is to present and study a method able to determine whether a predetermined model structure can be identified and that can be used in conjunction with another identification method to identify the system. The method that will be presented is based on differential algebra and is known as Ritt algorithm. The Ritt’s algorithm transforms a predetermined model structure in linear regression in the parameters from which one can use the least squares method or instrumental variables to identify the system. We will present some case studies and realise the analysis of identifiability for each case. For some cases we will identify the system, and then present a study for the consistency and precision of the estimates.

Although nonlinear model predictive control (NMPC) might be the best choice for a nonlinear plant, it is still not widely used. This is mainly due to the computational burden associated with solving online a set of nonlinear differential equations and a nonlinear dynamic optimization problem in real time. This thesis is concerned with strategies aimed at reducing the computational burden involved in different stages of the NMPC such as optimization problem, state estimation, and nonlinear model identification. A major part of the computational burden comes from function and derivative evaluations required in different parts of the NMPC algorithm. In this work, the problem is tackled using a recently introduced efficient tool, the automatic differentiation (AD). Using the AD tool, a function is evaluated together with all its partial derivative from the code defining the function with machine accuracy. A new NMPC algorithm based on nonlinear least square optimization is proposed. In a first–order method, the sensitivity equations are integrated using a linear formula while the AD tool is applied to get their values accurately. For higher order approximations, more terms of the Taylor expansion are used in the integration for which the AD is effectively used. As a result, the gradient of the cost function against control moves is accurately obtained so that the online nonlinear optimization can be efficiently solved. In many real control cases, the states are not measured and have to be estimated for each instance when a solution of the model equations is needed. A nonlinear extended version of the Kalman filter (EKF) is added to the NMPC algorithm for this purpose. The AD tool is used to calculate the required derivatives in the local linearization step of the filter automatically and accurately. Offset is another problem faced in NMPC. A new nonlinear integration is devised for this case to eliminate the offset from the output response. In this method, an integrated disturbance model is added to the process model input or output to correct the plant/model mismatch. The time response of the controller is also improved as a by–product. The proposed NMPC algorithm has been applied to an evaporation process and a two continuous stirred tank reactor (two–CSTR) process with satisfactory results to cope with large setpoint changes, unmeasured severe disturbances, and process/model mismatches. When the process equations are not known (black–box) or when these are too complicated to be used in the controller, modelling is needed to create an internal model for the controller. In this thesis, a continuous time recurrent neural network (CTRNN) in a state–space form is developed to be used in NMPC context. An efficient training algorithm for the proposed network is developed using AD tool. By automatically generating Taylor coefficients, the algorithm not only solves the differentiation equations of the network but also produces the sensitivity for the training problem. The same approach is also used to solve online the optimization problem of the NMPC. The proposed CTRNN and the predictive controller were tested on an evaporator and two–CSTR case studies. A comparison with other approaches shows that the new algorithm can considerably reduce network training time and improve solution accuracy. For a third case study, the ALSTOM gasifier, a NMPC via linearization algorithm is implemented to control the system. In this work a nonlinear state–space class Wiener model is used to identify the black–box model of the gasifier. A linear model of the plant at zero–load is adopted as a base model for prediction. Then, a feedforward neural network is created as the static gain for a particular output channel, fuel gas pressure, to compensate its strong nonlinear behavior observed in open–loop simulations. By linearizing the neural network at each sampling time, the static nonlinear gain provides certain adaptation to the linear base model. The AD tool is used here to linearize the neural network efficiently. Noticeable performance improvement is observed when compared with pure linear MPC. The controller was able to pass all tests specified in the benchmark problem at all load conditions.

Monitoramento da integridade estrutural (Structural health monitoring - SHM) está relacionado à implementação de alguma estratégia para a detecção de dano em estruturas de engenharia. Este estudo geralmente envolve a observação do sistema no tempo, utilizando amostras periódicas de medições da resposta dinâmica, a partir de um grupo de sensores, a fim de verificar alterações nos parâmetros modais, que podem indicar a presença do dano. Entretanto, especialmente para estruturas treliçadas, este processo tornase difícil principalmente porque nem todos os deslocamentos ou rotações nodais modelados numericamente podem ser medidos experimentalmente. Desta forma, o presente estudo tem por objetivo tratar algumas das ainda correntes questões dos sistemas de monitoramento da integridade estrutural baseados em registros de vibração. Primeiramente aborda-se um tema que, apesar de recentemente ter se mostrado importante, ainda apresenta muito poucos estudos: a influência da variação dos efeitos ambientais, especialmente a temperatura, sobre as características dinâmicas de estruturas. Com o intuito de verificar tal influência em pontes metálicas, os resultados apresentados por Ni et al. (2005) são utilizados para a realização de estudos de correlação, através de uma comparação entre equações de regressão linear e um modelo, proposto no presente trabalho, em Redes Neurais Artificiais (RNA). A seguir são estudados procedimentos de identificação estocástica de sistemas, passo fundamental para o monitoramento da integridade estrutural. Realiza-se uma revisão bibliográfica nesta área abordando a evolução dos métodos que utilizam apenas dados de resposta para a identificação. Enfoque principal é dado nos métodos de identificação estocástica de subespaço (SSI), pois se mostram os mais práticos e robustos para a determinação dos parâmetros modais da estrutura.Finalmente, o método dos vetores de localização de dano (Damage locating vector method- DLV), introduzido por Bernal (2002), é extensivamente discutido. Esta é umatécnica eficaz quando operando com um número arbitrário de sensores, modos truncados e em cenários de dano múltiplo, mantendo as operações numéricas simples. Além disto, a influência do ruído na precisão do método dos vetores de localização de dano é avaliada. Com o intuito de verificar o comportamento do método DLV perante diferentes intensidades de dano e, principalmente, na presença de ruído de medição, um estudo paramétrico é conduzido. Distintas excitações, como também diferentes cenários de dano, são numericamente testadas em uma treliça Warren contínua considerando um limitado conjunto de sensores, através de cinco níveis de ruído. Além disto, é proposto um caminho alternativo para determinar os vetores de localização de dano no procedimento do método DLV. A idéia é oferecer uma opção alternativa para a solução do problema utilizando um método algébrico amplamente difundido. A formulação original via decomposição em valores singulares é subsituída pela solução mais trivial de um problema de valores próprios. Isto é possível graças à relação algébrica entre a decomposição em valores singulares de uma matriz e a solução do problema de autovalores desta matriz pré-multiplicada por sua transposta. Os resultados finais mostraram que o método DLV, considerando a soluça alternativa, foi capaz de corretamente localizar as barras danificadas, utilizando dados somente de resposta da estrutura, mesmo considerando pequenas intesidades de dano e moderados níveis de ruído. / Structural health monitoring (SHM) refers to the implementation of some strategy for damage detection in engineering structures. This study generally involves the observation of a system over time using periodically sampled dynamic response measurements from a set of sensors in order to verify changes in modal parameters, which may indicate damage or degradation. However, especially for truss structures this process sounds difficulty mainly because not all nodal displacements or rotations in the numerical model can be experimentally measured. In this context, the present thesis aims to address some still current issues of the vibration-based structural health monitoring systems. Firstly it is introduced a subject that, although has recently shown important, still presents very few studies: the environmental effects, mainly temperature, on the structural modal properties. Seeking to address this influence on steel bridges, the results presented by Ni et al. (2005) are used to conduct correlations studies, comparing linear equation regression with an artificial neural network model (ANN), proposed in the present thesis. Procedures for stochastic systems identification are studied next, which is a fundamental phase for the SHM systems. A literature review in this field addressing the evolution of the methods that just use response data for identification is carried out. Main focus is given in the stochastic subspace identification methods (SSI), because they have been known as the most practical and robust methods to determine the structure’s modal parameters. Finally, the damage locating vector (DLV) method, introduced by Bernal (2002), is extensively discussed. This is a useful approach because is effective when operating with an arbitrary number of sensors, a truncated modal basis and multiple damage scenarios, while keeping the calculation at a low level. In addition, the noise influence on the accuracy of the damage locating vector method is evaluated. In order to verify the DLV behavior in front of different damages intensities and, mainly, in presence of measurement noise, a parametric study had been carried out. Different excitations as well as damagescenarios are numerically tested in a continuous Warren truss structure with a set of limited measurement sensors through five noise levels. Besides this, it is proposed another way to determine the damage locating vectors in the DLV procedure. The idea is to offer an alternative option to solve the problem with a more widespread algebraic method. The original formulation via singular value decomposition (SVD) is replaced by a common solution of an eigenvector and eigenvalue problem. This is possible thanks to the algebraic relationship between the singular value decomposition of a matrix and the eigenproblem solution of this matrix pre-multiplied by its transpose. The final results show that the DLV method, adopting the alternative, was able to correct locate the damaged bars, using an output-only system identification procedure, even considering small intensities of damage and moderate noise levels.

abstract: Buck converters are electronic devices that changes a voltage from one level to a lower one and are present in many everyday applications. However, due to factors like aging, degradation or failures, these devices require a system identification process to track and diagnose their parameters. The system identification process should be performed on-line to not affect the normal operation of the device. Identifying the parameters of the system is essential to design and tune an adaptive proportional-integral-derivative (PID) controller. Three techniques were used to design the PID controller. Phase and gain margin still prevails as one of the easiest methods to design controllers. Pole-zero cancellation is another technique which is based on pole-placement. However, although these controllers can be easily designed, they did not provide the best response compared to the Frequency Loop Shaping (FLS) technique. Therefore, since FLS showed to have a better frequency and time responses compared to the other two controllers, it was selected to perform the adaptation of the system. An on-line system identification process was performed for the buck converter using indirect adaptation and the least square algorithm. The estimation error and the parameter error were computed to determine the rate of convergence of the system. The indirect adaptation required about 2000 points to converge to the true parameters prior designing the controller. These results were compared to the adaptation executed using robust stability condition (RSC) and a switching controller. Two different scenarios were studied consisting of five plants that defined the percentage of deterioration of the capacitor and inductor within the buck converter. The switching logic did not always select the optimal controller for the first scenario because the frequency response of the different plants was not significantly different. However, the second scenario consisted of plants with more noticeable different frequency responses and the switching logic selected the optimal controller all the time in about 500 points. Additionally, a disturbance was introduced at the plant input to observe its effect in the switching controller. However, for reasonable low disturbances no change was detected in the proper selection of controllers. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

abstract: Microbial fuel cells(MFC) use micro-organisms called anode-respiring bacteria(ARB) to convert chemical energy into electrical energy. This process can not only treat wastewater but can also produce useful byproduct hydrogen peroxide(H2O2). Process variables like anode potential and pH play important role in the MFC operation and the focus of this dissertation are pH and potential control problems. Most of the adaptive pH control solutions use signal-based-norms as cost functions, but their strong dependency on excitation signal properties makes them sensitive to noise, disturbances, and modeling errors. System-based-norm( H-infinity) cost functions provide a viable alternative for the adaptation as they are less susceptible to the signal properties. Two variants of adaptive pH control algorithms that use approximate H-infinity frequency loop-shaping (FLS) cost metrics are proposed in this dissertation. A pH neutralization process with high retention time is studied using lab scale experiments and the experimental setup is used as a basis to develop a first-principles model. The analysis of such a model shows that only the gain of the process varies significantly with operating conditions and with buffering capacity. Consequently, the adaptation of the controller gain (single parameter) is sufficient to compensate for the variation in process gain and the focus of the proposed algorithms is the adaptation of the PI controller gain. Computer simulations and lab-scale experiments are used to study tracking, disturbance rejection and adaptation performance of these algorithms under different excitation conditions. Results show the proposed algorithm produces optimum that is less dependent on the excitation as compared to a commonly used L2 cost function based algorithm and tracks set-points reasonably well under practical conditions. The proposed direct pH control algorithm is integrated with the combined activated sludge anaerobic digestion model (CASADM) of an MFC and it is shown pH control improves its performance. Analytical grade potentiostats are commonly used in MFC potential control, but, their high cost (>$6000) and large size, make them nonviable for the field usage. This dissertation proposes an alternate low-cost($200) portable potentiostat solution. This potentiostat is tested using a ferricyanide reactor and results show it produces performance close to an analytical grade potentiostat. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

An accurate estimate of the gasturbine inlet air temperature is essential to the stability of the engine since its control depends on it. Most supersonic military aircrafts have a design with the engine integrated in the fuselage which requires a rather long inlet duct from the inlet opening to the engine face. Such duct can affect the temperature measurement because of the heat flow between the inlet air and the duct skin. This is especially true when the temperature sensor is mounted close to the duct skin, which is the case for most engines. This master thesis project therefore revolved around developing a method to better estimate the engine inlet temperature and to compensate for the disturbances which a temperature sensor near the duct skin can be exposed to. A grey box model of the system was developed based on heat transfer equations between different components in the inlet, as well as predictions of temperature changes based on a temperature model of the atmosphere and thermodynamic laws. The unknown parameters of the grey box model were estimated using flight data and tuned to minimize the mean square of the prediction error. The numerical optimization of the parameters was performed using the Matlab implementations of the BFGS and SQP algorithms. An extended Kalman filter based on the model was also implemented. The two models were then evaluated in terms of how much the mean squared error was reduced compared to just using the sensor measurement to estimate the inlet air temperature. It was also analyzed how much the models reduced the prediction errors. A cross-correlation analysis was also done to see how well the model utilized the input signals. The results show that the engine inlet temperature can be estimated with good accuracy. The two models were shown to reduce the mean square of the prediction error by between 84 % and 89 % if you compare with just using the temperature sensor to estimate the temperature. The model which utilized the Kalman filtering was shown to perform slightly better than the other model. The relevance of different subcomponents of the model were investigated in order to see if the model could be simplified and maintain similar accuracy. Some investigations were also done with the relationship between different temperatures of the inlet to further understand the flow patterns of the inlet and to perhaps improve the model even more in the future. / En korrekt uppskattning av lufttemperaturen vid inloppet till turbofläktmotorer är väsentlig för stabil motorfunktion eftersom den direkt påverkar motorregleringen. För militära flygplan där motorn är integrerad i flygplansskrovet krävs ofta en relativt lång luftkanal för att leda luften till motorn. En sådan kanal kan påverka temperaturmätningen på grund av det värmeutbyte som sker mellan luften i kanalen och kanalväggen, speciellt då temperaturgivaren placeras nära kanalväggen eftersom den då kan påverkas av temperaturgränsskiktet nära kanalväggen. Det här examensarbetet handlade därför om att utveckla en metod för att bättre skatta temperaturen i motorinloppet och kompensera för de störningar som en temperaturgivare nära kanalväggen kan utsättas för. En fysikalisk model av systemet togs fram baserat på värmeöverföringen mellan olika komponenter i luftintagskanalen, samt ett sätt att förutse temperaturändringar baserat på en generell temperaturmodell för atmosfären och termodynamiska lagar. Många parametrar i den fysikaliska modellen av systemet var dock okända så dessa skattades baserat på flygdata. Parametrarna anpassades till modellen på ett sådant sätt att den genomsnittliga kvadraten av modellens skattningsfel minimerades. Den numeriska optimeringen av parametrarna utfördes med hjälp av Matlabs implementation av BFGS- och SQP-algoritmerna. Ett utökat kalmanfilter baserat på modellen implementerades också. De två modellerna utvärderades i termer av hur mycket de reducerade kvadraten av skattningsfelet och jämfördes med att endast använda temperaturmätningarna för att skatta temperaturen. Det undersöktes även hur mycket skattningsfelen reducerades. Korskorrelationen mellan skattningsfelet och insignalerna undersöktes även för att se om modellen hade utnyttjat insignalerna på ett bra sätt. Resultaten visar att det går att skatta temperaturen i motorinloppet med god noggrannhet. De två modellerna visade sig reducera den genomsnittliga kvadraten av skattningsfelet med mellan 84 % och 89 % om man jämför med att bara använda temperaturgivaren för att skatta temperaturen. Den modell som utnyttjade kalmanfiltrering visade sig ge något bättre resultat än den andra modellen. Olika delmodellers relevans undersöktes för att se om modellen kunde förenklas utan att modellens noggrannhet äventyrades. Några tester utfördes även för att undersöka förhållandet mellan olika temperaturer i intaget. Detta för att få en bättre förståelse för strömningen i intaget och resultatet skulle eventuellt kunna användas för att förbättra modellen ytterligare i framtiden.

Alternative diesel fuels have been the subject of extensive investigation. Fatty acid methyl ester (FAME) based Biodiesel manufactured from vegetable oils or animal fats is an excellent candidate to replace common diesel fuel being renewable, non-toxic and often giving rise to reduced exhaust gas emissions. The transesterification process has been commonly and widely used to produce biodiesel from vegetable oil or animal fat. Vegetable oils or animal fats generally have viscosities higher than standard diesel oil. This means that it is necessary to reduce the viscosity by means of reacting vegetable oil with alcohol in the presence of a suitable catalyst. The target product for this reaction is methyl ester, with glycerol and potentially soap produced as by products with the process of transesterification. Methylester (Biodiesel) is produced by converting triglycerides to alkylesters. A batch transesterification process has two significant mechanisms, and exhibits a mass transfer controlled region that precedes a second order kinetically controlled region. In order to control the conversion process it is useful to employ process monitoring. In particular monitoring of the mass transfer processes that limits the initial reaction rates could prove to be beneficial in allowing for process optimization and control. This thesis proposes the use of a new method of biodiesel process monitoring using low frequency (15kHz) impedance sensing which is able to provide information regarding the progress of mass transfer and chemical reaction during biodiesel production. An interdigitated (ID) sensor has been used to monitoring the biodiesel process The ID sensor is of simple construction and consists of two sets of interleaved electrodes (fingers). The two sets of electrodes are separated by a gap and when an AC excitation voltage is applied across the interleaved electrodes an oscillating electric field is developed. The response of the fluid surrounding the sensor to the applied excitation was then used to determine progress of the chemical reaction by evaluating the real and complex impedance. A significant and unambiguous change in the components of impedance has been shown to occur during mixing (mass transfer) and transesterification. The impedance measurements gained during transesterification were then used for the development of a system model. A systematic approach was used to select mathematical models and system identification techniques were evaluated. The system identification investigation used real process measurement data in conjunction with the Matlab system identification toolbox.