Browsing by Subject "Kalman-Filter"

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    Development of software sensors for on-line monitoring of baker’s yeast fermentation process
    (2021) Yousefi-Darani, Abdolrahim; Hitzmann, Bernd
    Software sensors and bioprocess are well-established research areas which have much to offer each other. Under the perspective of the software sensors area, bioprocess can be considered as a broad application area with a growing number of complex and challenging tasks to be dealt with, whose solutions can contribute to achieving high productivity and high-quality products. Although throughout the past years in the field of software sensors and bioprocess, progress has been quick and with a high degree of success, there is still a lack of inexpensive and reliable sensors for on-line state and parameter estimation. Therefore, the primary objective of this research was to design an inexpensive measurement system for on-line monitoring of ethanol production during the backer’s yeast cultivation process. The measurement system is based on commercially available metal oxide semiconductor gas sensors. From the bioreactor headspace, samples are pumped past the gas sensors array for 10 s every five minutes and the voltage changes of the sensors are measured. The signals from the gas sensor array showed a high correlation with ethanol concentration during cultivation process. In order to predict ethanol concentrations from the data of the gas sensor array, a principal component regression (PCR) model was developed. For the calibration procedure no off-line sampling was used. Instead, a theoretical model of the process is applied to simulate the ethanol production at any given time. The simulated ethanol concentrations were used as reference data for calibrating the response of the gas sensor array. The obtained results indicate that the model-based calibrated gas sensor array is able to predict ethanol concentrations during the cultivation process with a high accuracy (root mean square error of calibration as well as the percentage error for the validation sets were below 0.2 gL-1 and 7 %, respectively). However the predicted values are only available every five minutes. Therefore, the following plan of the research goal was to implement an estimation method for continues prediction of ethanol as well as glucose, biomass and the growth rates. For this reason, two nonlinear extensions of the Kalman filter namely the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) were implemented separately for state and parameter estimation. Both prediction methods were validated on three different cultivation with variability of the substrate concentrations. The obtained results showed that both estimation algorithms show satisfactory results with respect to estimation of concentrations of substrates 6 and biomass as well as the growth rate parameters during the cultivation. However, despite the easier implementation producer of the UKF, this method shows more accurate prediction results compared to the EKF prediction method. Another focus of this study was to design and implement an on-line monitoring and control system for the volume evaluation of dough pieces during the proofing process of bread making. For this reason, a software sensor based on image processing was designed and implemented for measuring the dough volume. The control system consists of a fuzzy logic controller which takes into account the estimated volume. The controller is designed to maintain the volume of the dough pieces similar to the volume expansion of a dough piece in standard conditions during the proofing process by manipulating the temperature of the proofing chamber. Dough pieces with different amounts of backer’s yeast added in the ingredients and in different temperature starting states were prepared and proofed with the supervision of the software sensor and the fuzzy controller. The controller was evaluated by means of performance criteria and the final volume of the dough samples. The obtained results indicate that the performance of the system is very satisfactory with respect to volume control and set point deviation of the dough pieces.
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    Four essays in the empirical analysis of business cycles and structural breaks
    (2015) Marczak, Martyna; Beißinger, Thomas
    Business cycle analysis has a long history in the macroeconomics literature and since its origins it poses a challenge for both empirical and theoretical research. The enduring interest in this research area is dictated by its high relevance for economic policy. Reliable information on the state of the economy plays a crucial role in the monitoring of the economy and in the policy-making process. This involves the choice of the method for extraction of a proper business cycle indicator. Moreover, the business cycle analyst also has to take account of structural breaks as well as seasonal and higher frequency movements of the series that can affect the properties of a business cycle indicator. Another reason for the keen interest in empirical business cycle research can be seen in the need to validate theoretical approaches. A prominent example is the debate on the cyclical behavior of real wages which evolved to one of the most lively and long--lasting debates in macroeconomics. This thesis tries to contribute to the literature under the aforementioned aspects. It offers a new methodological perspective with respect to the extraction of business cycles and detection of structural breaks. Furthermore, it sheds some light on the question of real wage cyclicality from the empirical point of view. The first essay proposes a new multivariate model based on a band-pass filter to construct business cycle indicators. Using this method and a dataset with monthly and quarterly US time series, two monthly business cycle indicators are obtained for the US. It is shown that the proposed method not only reproduces historical recessions very well, but it also performs good in terms of forecasting. The second essay for the first time in the literature combines indicator saturation as a general-to-specific approach to detect outliers and structural breaks with the structural time series model for the purpose of seasonal adjustment. The performance of the impulse-indicator and step-indicator saturation for detecting additive outliers and level shifts is tested in both a comprehensive Monte Carlo simulation exercise and an empirical application. The latter involves five European industrial production series. Its focus lies on the question whether the recessionary episode starting towards the end of 2008 can be described by the inherent model dynamics, or whether it represents a major structural change. In the third essay, stylized facts about the cyclicality of real consumer wages and real producer wages in Germany are established. First, various detrending methods are applied to estimate a business cycle and real wage cycles. The comovements between real wage cycles and the business cycle are then examined both in the time domain and in the frequency domain by resorting to the concept of the phase angle. According to the frequency domain results, the consumer real wage lags behind the business cycle. Moreover, it exhibits an anticyclical behavior in the short run, whereas in the longer run a procyclical behavior can be observed. For the producer real wage, in contrast, the results in the frequency domain are not clear-cut. The fourth essay compares the cyclical behavior of consumer and producer real wages in the USA and Germany. This study is the first one which employs wavelet analysis as a comovement tool in the context of the examined research question. From the findings of this study it can be inferred that the USA and Germany differ with respect to the lead-lag relationship of real wages and the business cycle. In the USA, both real wages are leading the business cycle in the entire time interval. The German consumer real wage is, on the other hand, lagging the business cycle. For the German producer real wage, the lead-lag pattern changes over time. In addition, the results show that real wages in the USA as well in Germany are procyclical or acyclical until 1980 and countercyclical thereafter.
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    International interest-rate risk premia in affine term structure models
    (2009) Geiger, Felix
    I estimate a Gaussian two-factor affine term structure model of bond yields for three countries, the United States, the United Kingdom and Germany. I find a considerable time-varying component of excess returns in the data. They are positively correlated with the slope of the term structure and negatively with the short-term policy rate. In addition, the panel clearly indicates to co-movements in the same directions on an international level. When testing the estimated model for the expectations puzzle of the the term structure, at least at one end of the yield curve, this puzzle can be resolved when applying risk-adjusted yield changes.