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abstract: Behavior-driven obesity has become one of the most challenging global epidemics since the 1990s, and is presently associated with the leading causes of death in the U.S. and worldwide, including diabetes, cardiovascular disease, strokes, and some forms of cancer. The use of system identification and control engineering principles in the design of novel and perpetually adaptive behavioral health interventions for promoting physical activity and healthy eating has been the central theme in many recent contributions. However, the absence of experimental studies specifically designed with the purpose of developing control-oriented behavioral models has restricted prior efforts in this domain to the use of hypothetical simulations to demonstrate the potential viability of these interventions. In this dissertation, the use of first-of-a-kind, real-life experimental results to develop dynamic, participant-validated behavioral models essential for the design and evaluation of optimized and adaptive behavioral interventions is examined. Following an intergenerational approach, the first part of this work aims to develop a dynamical systems model of intrauterine fetal growth with the prime goal of predicting infant birth weight, which has been associated with subsequent childhood and adult-onset obesity. The use of longitudinal input-output data from the “Healthy Mom Zone” intervention study has enabled the estimation and validation of this fetoplacental model. The second part establishes a set of data-driven behavioral models founded on Social Cognitive Theory (SCT). The “Just Walk” intervention experiment, developed at Arizona State University using system identification principles, has lent a unique opportunity to estimate and validate both black-box and semiphysical SCT models for predicting physical activity behavior. Further, this dissertation addresses some of the model estimation challenges arising from the limitations of “Just Walk”, including the need for developing nontraditional modeling approaches for short datasets, as well as delivers a new theoretical and algorithmic framework for structured state-space model estimation that can be used in a broader set of application domains. Finally, adaptive closed-loop intervention simulations of participant-validated SCT models from “Just Walk” are presented using a Hybrid Model Predictive Control (HMPC) control law. A simple HMPC controller reconfiguration strategy for designing both single- and multi-phase intervention designs is proposed. / Dissertation/Thesis / Doctoral Dissertation Chemical Engineering 2021

Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2022 / Using the ARFIMA (autoregressive and fractionally integrated moving aver age) model extended with sGARCH (standard generalised autoregressive con ditional heteroscedasticity) and ’gjrGARCH (Glosten-Jagannathan-Runkle gen eralised autoregressive conditional heteroscedascity) innovations, fractional in tegration approach and state space model, this study has empirically examined persistency of inflation dynamics of Ghana and South Africa, the only two coun tries in Sub-Saharan Africa with Inflation Targeting (IT) monetary policy. The first part of the analysis employed monthly CPI (Consumer Price Index) in flation series for the period January 1971 to October 2014 obtained from the Bank of Ghana (BoG), and for the period January 1995 to December 2014 ob tained from Statistics South Africa. The second part involves the estimation of threshold effect of inflation on economic growth using annual data obtained from the IMF (International Monetary Fund) database for the period 1981 to 2014, for both countries. Results from the study showed that structural breaks, long memory and non linearities (or regime shifts) are largely responsible for inflation persistence, hence the ever-changing nature of inflation rates of Ghana and South Africa. ARFIMA(3,0.35,1)-‘gjrGARCH(1,1) under Generalised Error Distribution (GED) and ARFIMA(3,0.50,1)-‘gjrGARCH(1,1) under Student-t Distribution (STD) mod els provided the best fit for persistence in the conditional mean (or level) of CPI for Ghana and South Africa, respectively. The results from these models pro vided evidence of time-varying conditional mean and volatility in CPI inflation rates of both countries. The two models also revealed an asymmetric effect of inflationary shocks, where negative shocks appear to have greater impact than positive shocks, in terms of persistence on the conditional mean with time varying volatility. This thesis proposes a model that combines fractional integration with non linear deterministic terms based on the Chebyshev polynomials in time for the analysis of CPI inflation rates of Ghana and South Africa. We tested for non-linear deterministic terms in the context of fractional integration and esti mated the fractional differencing parameters, d to be 1.11 and 1.32 respectively, for the Ghanaian and the South African inflation rates, but the non-linear trends were found to be statistically insignificant in the two series. New ev idence from this thesis depicts that inflation rate of Ghana is highly persistent and non-mean reverting, with an estimated fractional differencing parameter, d > 1.0, and will therefore require some policy action to steer inflation back to stability. However, the South African inflation series was found to be a cyclical process with an order of integration estimated to be d = 0.7, depicting mean reversion, with the length of the cycles approximated to last for 80 months. Finally, the thesis incorporated structural breaks, long memory, non-linearity, and some explanatory variables into a state space model and estimated the threshold effect of inflation on economic growth. The empirical results suggest that inflation below the estimated levels of 9% and 6% for Ghana and South Africa respectively, will be conducive for economic growth. The policy implications of these results for both countries are as follows. First, both series had similar properties responsible for inducing inflation persistence such as structural breaks, non-linearities, long memory and asymmetric re sponse to negatives shocks - but with varied degrees of magnitude. For both countries, the conditional mean and unobserved components such as volatility for both countries were found to be time-varying. This thesis, therefore, recom mends to the BoG and the South African Reserve Bank (SARB) - responsible for monetary policies, and the Finance Ministers of both governments - respon sible for fiscal policies, to take the above-mentioned properties into account in the formulation of their monetary policies. Second, the thesis recommends that the BoG and the SARB consolidate the IT policy, since keeping inflation below the targets set of 9% and 6%, respectively for Ghana and South Africa, will boost economic growth. Third, policymakers could also design measures (monetary and fiscal policies) such as increase in interest rates, credit control, and reduction of unnecessary expenditure, among others, to control inflation due to its adverse effects on market volatility. Even though an increase in interest rates could assist in curtailing the recent and anticipated increase in inflation rates in both countries, where targets have been missed by Ghana and South Africa, it will also be prudent to legislate monetary policies around demand-supply side since the problem of both coun tries appears to be more of a structuralist than a monetarist. It is, therefore, recommended that both countries tighten the IT monetary policy in order to re duce inflation persistence. This will eventually impact on poverty and income distribution with ramifications for economic growth and/or development. The fourth implication of these results is that governments and central banks should be mindful of the actions and decisions they take, in the sense that unguarded decisions and unnecessary alarms could raise uncertainties in the economy, which could, in turn, affect the future trajectory of inflation. Finally, the thesis recommends that governments of both countries strengthen the pri vate sector, which is the engine of growth. For small and open economies such as Ghana and South Africa, this will grow the economy through job creation and restore investor confidence. / National Research Foundation (NRF), Department of Science and Technology (DST), Telkom’s Tertiary Education Support Programme (TESP) and the NRF-DST Centre of Excellence for Mathematical and Statistical Sciences (CoE-MaSS)

Die vorliegende Arbeit ist motiviert durch die breite Anwendung von Schwenkantrieben in vielfältigen konventionellen und neuen Technologiefeldern: In Windenergieanlagen führen Schwenkantriebe die Gondel samt Rotor der momentanen Windrichtung nach. Bei Radioteleskopen erlauben sie die hochpräzise azimutale Ausrichtung der Parabolantenne. Und im Sektor der Baumaschinen kommen sie zum Schwenken der Ausleger von Kranen und fördertechnischen Großgeräten zum Einsatz. Trotz des zunächst einfach erscheinenden Aufbaus der Schwenkantriebssysteme erweisen sich sowohl ihre mechanische Dimensionierung als auch ihre sichere Betriebsführung als herausfordernd. So belegen Messdaten und Betriebserfahrungen die Neigung der Antriebsstränge zu niederfrequenten Drehschwingungen. Außerdem treten große Spitzenlasten während der Schwenkrichtungsumkehr in den Getriebestufen auf. In diesem Forschungsbeitrag werden Methoden vorgestellt, mit denen elektromechanische Schwenkantriebssysteme modelliert, dynamisch analysiert und regelungstechnisch optimiert werden können. Dazu wird der schwingungsfähige mechanische Antriebsstrang eines Beispielschwenkwerks als detailliertes Mehrkörpersystem-Simulationsmodell abgebildet. Um auch Wechselwirkungen mit den elastischen Umgebungsstrukturen, der Antriebsregelung und den Betriebslasten zu erfassen, wird ein domänenübergreifendes Modellierungsvorgehen verfolgt. Es erfolgt eine messtechnische Validierung des mechatronischen Gesamtsystemmodells. Mit dem Vorliegen treffsicherer Systemmodelle eröffnet sich die Möglichkeit, ein modellbasiertes Mehrgrößenregelverfahren (LQG) auszulegen und simulativ zu erproben. Im Vergleich zur bisherigen proportional-integralen (PI) Antriebsregelung verspricht dies die aktive Dämpfung von Triebstrangschwingungen bei gleichzeitiger Erhöhung der Arbeitsgeschwindigkeit. Um für beliebige elastische Antriebssysteme das Optimierungspotenzial abschätzen zu können, erfolgt ein systematischer Vergleich der beiden Regelstrategien. Anschließend wird ein praxisnahes Vorgehen zur Regelungsauslegung vorgestellt. Besonderer Fokus liegt neben der Robustheit auch auf der begrenzten Anzahl verfügbarer Sensoren bei industriellen Antrieben. Zudem wird auch das oftmals beträchtliche Getriebespiel als signifikante Nichtlinearität der Regelstrecke berücksichtigt. Um eine Reduktion der Spitzenlasten während der Drehrichtungsumkehr des Schwenkantriebes zu erreichen, wird abschließend ein Konzept zur zeit- und belastungsoptimierten Durchquerung des Getriebespiels erarbeitet. Da die konventionelle Drehzahlregelung des Schwenkantriebs hierbei nur um ein Zusatzmodul erweitert wird, bietet sich das Vorgehen insbesondere zur Ertüchtigung bestehender Antriebe an.:1 Einleitung 1.1 Motivation 1.2 Konkretisierte Problemstellung 1.3 Aufbau der Arbeit 2 Grundlagen und Forschungsstand 2.1 Modellbildung und Simulation von Antriebssystemen 2.1.1 Mehrkörpersystem-Simulation von Antriebssystemen 2.1.2 Modellbildung von Schwenkwerken 2.2 Anwendungsbereiche von Schwenkantrieben 2.2.1 Turmdrehkrane 2.2.2 Windenergieanlagen 2.2.3 Radioteleskope 2.2.4 Baumaschinen 2.3 Untersuchtes Beispielschwenkwerk 2.3.1 Antriebstechnik 2.3.2 Bisherige Untersuchungen an Schaufelradbaggern 3 Modellbildung und Simulation von Schwenkwerken 3.1 Mechanische Komponenten 3.1.1 Schwenkantriebe 3.1.2 Elastische Tragstrukturen am Getriebeausgang 3.1.3 Weitere Antriebsstränge des Gesamtsystems 3.2 Elektrische und informationsverarbeitende Domäne 3.2.1 Aktorik – Elektrische Antriebsmaschine 3.2.2 Informationsverarbeitung – Antriebsregelung 3.2.3 Informationserfassung – Winkelmesssysteme 3.3 Betriebslasten 3.3.1 Quasistatische Lasten 3.3.2 Simulation der bodenmechanischen Interaktion bei Schaufelradbaggern 3.4 Messdatengestützte Validierung der Systemmodelle 3.4.1 Beschreibung des Messaufbaus 3.4.2 Betriebsschwingungsanalyse 3.4.3 Validierung Schwenkwerk – Reversiervorgang 3.4.4 Validierung Gesamtsystem – Grab-Schwenk-Prozess 3.5 Ableitung eines mechanischen Minimalmodells 3.6 Zwischenfazit 4 Drehzahlregelung elastischer Antriebssysteme 4.1 Allgemeine Grundlagen 4.1.1 Führungs- und Störungsverhalten 4.1.2 Stabilität und Performanz 4.1.3 Singulärwertzerlegung von Frequenzgangmatrizen 4.2 Motor mit elastisch gekoppeltem Abtrieb 4.2.1 Proportional-Integrale Eingrößenregelung 4.2.2 Zustandsregelung 4.2.3 Generalisierter Vergleich der Regelungskonzepte 4.3 Erweiterung auf Mehrmotorenantriebe 4.4 Konzeption und Umsetzung einer Zustandsregelung 4.4.1 Auslegung eines optimalen Zustandsreglers 4.4.2 Rekonstruktion des Zustandsvektors bei Antrieben mit Verzahnungsspiel 4.4.3 Analyse des Gesamtkonzeptes 4.5 Zwischenfazit 5 Verzahnungsspiel in elastischen Antriebssträngen 5.1 Ursachen 5.2 Modellbildung 5.2.1 Klassische Modellierung als Totzone 5.2.2 Erweitertes Spielmodell nach Nordin 5.2.3 Hysterese 5.3 Auswirkungen 5.3.1 Antriebsstrangbelastung 5.3.2 Folgen auf Gesamtsystemebene 5.3.3 Zwischenfazit 5.4 Regelstrategien für spielbehaftete Antriebe 5.4.1 Lineare Eingrößenregelung 5.4.2 Mehrgrößenregelung – Zustandsraummethoden 5.4.3 Umschaltende lineare Regler 5.4.4 Modellprädiktive Regelung 5.4.5 Invertierung der Nichtlinearität 5.4.6 Zwischenfazit 5.5 Konzeption und Umsetzung einer Strategie zum lastminimierten Spieldurchlauf 5.5.1 Optimaltrajektorie zur Spieldurchquerung 5.5.2 Realisierung der Spieldurchquerung 5.5.3 Simulative Verifizierung 6 Zusammenfassung und Ausblick / The present work is motivated by the wide application of slewing drives and yaw drives in a variety of conventional and emerging fields of technology: In wind turbines, yaw drives track the nacelle and rotor according to the current wind direction. In radio telescopes, they enable high-precision azimuthal alignment of the parabolic antenna. And in the construction machinery sector, they are used to rotate the booms of cranes and bucket wheel excavators. At first glance the design of slewing drive systems seems to be simple, but their mechanical dimensioning as well as their reliable operation turn out to be challenging. Measurement data and operating experience show that the drive trains are prone to low-frequency torsional vibrations. In addition, large peak loads occur during reversals of the slewing direction. In this thesis, methods are presented for the modeling, dynamical analysis and control optimization of electromechanical slewing drive systems. Therefore, the mechanical drive train of an exemplary slewing gearbox unit is represented as a detailed multibody system simulation model. A cross-domain modeling approach is pursued in order to capture interactions with the surrounding flexible structures, the drive control and the operating loads as well. The resulting overall mechatronic system model is validated by measurement. The development of accurate system models enables a model-based multivariable control method (LQG) to be designed and tested by simulation. Compared to conventional proportional integral (PI) drive control, this promises active damping of drive train vibrations while simultaneously increasing the operating speed. To estimate the optimization potential for arbitrary elastic drive systems, a systematic comparison of both control strategies is performed. Subsequently, a practical procedure for designing the control system is presented. In addition to robustness, special focus is placed on the limited number of available sensors in industrial drives. Furthermore, the considerable gear backlash is also accounted for as a significant nonlinearity of the controlled system. To reduce peak loads during the reversal of the rotational direction, a novel approach for time- and load-optimized traversing of the gearbox backlash is developed. Since the conventional speed control algorithm is only extended by an additional module, the method is particularly suitable for retrofitting existing drives.:1 Einleitung 1.1 Motivation 1.2 Konkretisierte Problemstellung 1.3 Aufbau der Arbeit 2 Grundlagen und Forschungsstand 2.1 Modellbildung und Simulation von Antriebssystemen 2.1.1 Mehrkörpersystem-Simulation von Antriebssystemen 2.1.2 Modellbildung von Schwenkwerken 2.2 Anwendungsbereiche von Schwenkantrieben 2.2.1 Turmdrehkrane 2.2.2 Windenergieanlagen 2.2.3 Radioteleskope 2.2.4 Baumaschinen 2.3 Untersuchtes Beispielschwenkwerk 2.3.1 Antriebstechnik 2.3.2 Bisherige Untersuchungen an Schaufelradbaggern 3 Modellbildung und Simulation von Schwenkwerken 3.1 Mechanische Komponenten 3.1.1 Schwenkantriebe 3.1.2 Elastische Tragstrukturen am Getriebeausgang 3.1.3 Weitere Antriebsstränge des Gesamtsystems 3.2 Elektrische und informationsverarbeitende Domäne 3.2.1 Aktorik – Elektrische Antriebsmaschine 3.2.2 Informationsverarbeitung – Antriebsregelung 3.2.3 Informationserfassung – Winkelmesssysteme 3.3 Betriebslasten 3.3.1 Quasistatische Lasten 3.3.2 Simulation der bodenmechanischen Interaktion bei Schaufelradbaggern 3.4 Messdatengestützte Validierung der Systemmodelle 3.4.1 Beschreibung des Messaufbaus 3.4.2 Betriebsschwingungsanalyse 3.4.3 Validierung Schwenkwerk – Reversiervorgang 3.4.4 Validierung Gesamtsystem – Grab-Schwenk-Prozess 3.5 Ableitung eines mechanischen Minimalmodells 3.6 Zwischenfazit 4 Drehzahlregelung elastischer Antriebssysteme 4.1 Allgemeine Grundlagen 4.1.1 Führungs- und Störungsverhalten 4.1.2 Stabilität und Performanz 4.1.3 Singulärwertzerlegung von Frequenzgangmatrizen 4.2 Motor mit elastisch gekoppeltem Abtrieb 4.2.1 Proportional-Integrale Eingrößenregelung 4.2.2 Zustandsregelung 4.2.3 Generalisierter Vergleich der Regelungskonzepte 4.3 Erweiterung auf Mehrmotorenantriebe 4.4 Konzeption und Umsetzung einer Zustandsregelung 4.4.1 Auslegung eines optimalen Zustandsreglers 4.4.2 Rekonstruktion des Zustandsvektors bei Antrieben mit Verzahnungsspiel 4.4.3 Analyse des Gesamtkonzeptes 4.5 Zwischenfazit 5 Verzahnungsspiel in elastischen Antriebssträngen 5.1 Ursachen 5.2 Modellbildung 5.2.1 Klassische Modellierung als Totzone 5.2.2 Erweitertes Spielmodell nach Nordin 5.2.3 Hysterese 5.3 Auswirkungen 5.3.1 Antriebsstrangbelastung 5.3.2 Folgen auf Gesamtsystemebene 5.3.3 Zwischenfazit 5.4 Regelstrategien für spielbehaftete Antriebe 5.4.1 Lineare Eingrößenregelung 5.4.2 Mehrgrößenregelung – Zustandsraummethoden 5.4.3 Umschaltende lineare Regler 5.4.4 Modellprädiktive Regelung 5.4.5 Invertierung der Nichtlinearität 5.4.6 Zwischenfazit 5.5 Konzeption und Umsetzung einer Strategie zum lastminimierten Spieldurchlauf 5.5.1 Optimaltrajektorie zur Spieldurchquerung 5.5.2 Realisierung der Spieldurchquerung 5.5.3 Simulative Verifizierung 6 Zusammenfassung und Ausblick

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Heterogeneous data with different characteristics are ubiquitous in the modern digital world. For example, the observations collected from a process may change on its mean or variance. In numerous applications, data are often of mixed types including both discrete and continuous variables. Heterogeneity also commonly arises in data when underlying models vary across different segments. Besides, the underlying pattern of data may change in different dimensions, such as in time and space. The diversity of heterogeneous data structures makes statistical modeling and analysis challenging. Detection of change-points in heterogeneous data has attracted great attention from a variety of application areas, such as quality control in manufacturing, protest event detection in social science, purchase likelihood prediction in business analytics, and organ state change in the biomedical engineering. However, due to the extraordinary diversity of the heterogeneous data structures and complexity of the underlying dynamic patterns, the change-detection and analysis of such data is quite challenging. This dissertation aims to develop novel statistical modeling methodologies to analyze four types of heterogeneous data and to find change-points efficiently. The proposed approaches have been applied to solve real-world problems and can be potentially applied to a broad range of areas. / Ph. D. / Heterogeneous data with different characteristics are ubiquitous in the modern digital world. Detection of change-points in heterogeneous data has attracted great attention from a variety of application areas, such as quality control in manufacturing, protest event detection in social science, purchase likelihood prediction in business analytics, and organ state change in the biomedical engineering. However, due to the extraordinary diversity of the heterogeneous data structures and complexity of the underlying dynamic patterns, the change-detection and analysis of such data is quite challenging. This dissertation focuses on modeling and analysis of data with heterogeneous structures. Particularly, four types of heterogeneous data are analyzed and different techniques are proposed in order to nd change-points efficiently. The proposed approaches have been applied to solve real-world problems and can be potentially applied to a broad range of areas.

This master’s thesis investigates the possibility of replacing the traditional triple cascaded Proportional-Integral (PI) controller architecture, used to regulate a PermanentMagnet Synchronous Motor (PMSM), with a state-space approach. Using theory regarding PMSMs and Electromechanical Actuators (EMAs) as a foundation, the thesisdescribes the design process of the proposed control methods up until implementation. The two state-space approaches evaluated in the thesis are: a single Linear-QuadraticRegulator (LQR) method and a torque reference generating LQR together with a setof two PI controllers for current regulation. Evaluation of the chosen methods wasdone based on simulations in Simulink/Simscape, containing verified models mimicking real hardware, with several input cases. Based on simulation results, the combined LQR and PI method was deemed promisingto replace the current cascaded PI control architecture. The open end of the reportallows for further implementation and evaluation on the real platform to confirm theresults obtaiend through simulations.

Linear time-invariant (LTI) dynamic networks are described by their dynamical structure function, and generally, they have many possible state space realizations. This work characterizes the necessary and sufficient conditions on a state transformation that preserves the dynamical structure function, thereby generating the entire set of realizations of a given order for a specific dynamic network.

Stavové modely jsou neobyčejně užitečné v mnoha inženýrských a vědeckých oblastech. Jejich atraktivita vychází především z toho faktu, že poskytují obecný nástroj pro popis široké škály dynamických systémů reálného světa. Nicméně, z důvodu jejich obecnosti, přidružené úlohy inference parametrů a stavů jsou ve většině praktických situacích nepoddajné. Tato dizertační práce uvažuje dvě zvláště důležité třídy nelineárních a ne-Gaussovských stavových modelů: podmíněně konjugované stavové modely a Markovsky přepínající nelineární modely. Hlavní rys těchto modelů spočívá v tom, že---navzdory jejich nepoddajnosti---obsahují poddajnou podstrukturu. Nepoddajná část požaduje abychom využily aproximační techniky. Monte Carlo výpočetní metody představují teoreticky a prakticky dobře etablovaný nástroj pro řešení tohoto problému. Výhoda těchto modelů spočívá v tom, že poddajná část může být využita pro zvýšení efektivity Monte Carlo metod tím, že se uchýlíme k Rao-Blackwellizaci. Konkrétně, tato doktorská práce navrhuje dva Rao-Blackwellizované částicové filtry pro identifikaci buďto statických anebo časově proměnných parametrů v podmíněně konjugovaných stavových modelech. Kromě toho, tato práce adoptuje nedávnou particle Markov chain Monte Carlo metodologii pro návrh Rao-Blackwellizovaných částicových Gibbsových jader pro vyhlazování stavů v Markovsky přepínajících nelineárních modelech. Tyto jádra jsou posléze použity pro inferenci parametrů metodou maximální věrohodnosti v uvažovaných modelech. Výsledné experimenty demonstrují, že navržené algoritmy překonávají příbuzné techniky ve smyslu přesnosti odhadu a výpočetního času.

The diploma thesis deals with the use of a simulation model for the development of an automatic algorithm for the creation of a routing table and route evaluation in a transport system. It includes a search of modeling and simulation issues and state-space search issues with an analysis of available search methods. The simulation model of the transport system is created in the software Tecnomatix Plant Simulation, where an algorithm for automatic creation of routing tables for routing and evaluation of routes according to static criteria is subsequently developed and tested. The work presents a proposal for the principle of the algorithm for evaluating the routes of the transport system, including dynamic criteria and their optimization.