Eldorado - Repository of the TU Dortmund
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Towards encrypted cloud-based control-as-a-service
(2024) Schlüter, Nils; Schulze Darup, Moritz; Ferrari, Riccardo
The increasing interconnectivity of control systems paves the way for exciting new opportunities, such as cloud-based control services. At the same time, connected control systems are susceptible to cyberattacks and data leakage.
Therefore, this dissertation aims to enhance the security of cyberphysical systems by ensuring the confidentiality of control data during its evaluation. % on external platforms.
To achieve this, advanced cryptographic techniques such as homomorphic encryption and secure multi-party computation are utilized, which enable computations on encrypted data. However, the development of novel encrypted controllers results in unique interdisciplinary challenges that necessitate a nuanced approach, blending elements of cryptography and control theory.
The first section of this thesis is devoted to iterative control algorithms. First, cloud-based dynamic controllers are considered. These are based on a linear iteration, which can lead to a numerical overflow in an encrypted evaluation. Our system-theoretic analysis reveals that a specific subset of dynamic controllers, which can be efficiently encrypted, is not affected by this problem.
Second, privacy in consensus problems of multi-agent systems is explored.
In the related algorithms, we address iterations and a mechanism to control the data access.
The subsequent section of this thesis focuses on controllers that use non-po\-ly\-no\-mi\-al functions, where model predictive control is a prominent example. Encrypted implementations of these functions are often inefficient.
Our novel approach uses max-out neural networks, which form a versatile basis to approximate any continuous function. Moreover, they are well-aligned with primitives from secure multi-party computation, resulting in an efficient implementation.
The final section conducts a security analysis of random affine transformations. Although these transformations have gained significant popularity, they currently do not offer a technically sound security guarantee.
The aforementioned results are numerically validated and illustrated with relevant examples. Although significant progress has been made, further efficiency improvements are paramount for the practical application of encrypted control.
Extending the distributional regression framework
(2025) Briseño Sanchez, Guillermo; Groll, Andreas; Klein, Nadja
This thesis develops distributional regression methods tailored to the estimation of treatment effects as well as joint modelling of multivariate non-commensurable responses, all based on the Generalised Additive Models for Location Scale and Shape (GAMLSS) approach. In addition, it postulates methods for data-driven variable selection for the aforementioned model class. These developments are introduced across four contributed articles and are implemented in the statistical programming software R.
In the first article, we derive treatment effects on the entire conditional response distribution via an instrumental variable estimation approach based on GAMLSS. Our approach allows to model all parameters of possibly complex outcome distributions as well as non-linear relationships between explanatory variables, instrument and outcome of interest. This demonstrates the potential of using distributional regression in instrumental variable regression both to account for endogeneity and estimate treatment effects beyond the mean.
The second article introduces flexible copula-based statistical models for bivariate responses comprised of non-commensurate (i.e. mixed) variables whose components are a right-censored time-to-event response and a non-time-to-event outcome. The copula approach allows for separate specification of the dependence structure between the margins and their individual distribution functions. The model of the time-to-event margin is constructed via discrete-time-to-event or piecewise-exponential methods using the correspondence of their likelihood of the aforementioned approaches with well-known univariate distributions.
The last two articles tackle the issue of data-driven variable selection for copula-based distributional regression models. In the third article we devise a gradient boosting estimation algorithm adapted to accommodate copula models with arbitrary marginal distributions suited for bivariate binary, count and non-commensurable mixed outcomes. The last article further extends these methods to bivariate right-censored time-to-event responses. This dramatically streamlines the model-building process for a wide range of response structures.
The versatility of the proposed methods is demonstrated through the analysis of various synthetic and real data structures from labour economics, transportation, genetic epidemiology, healthcare utilisation, childhood undernutrition and ovarian cancer.
Kondo breakdown in multi-orbital Anderson lattices induced by destructive hybridization interference
(2024-09-02) Eickhoff, Fabian; Anders, Frithjof B.
In this paper we consider a multi band extension to the periodic Anderson model. We use a single site DMFT(NRG) in order to study the impact of the conduction band mediated effective hopping of the correlated electrons between the correlated orbitals onto the heavy Fermi liquid formation. Whereas the hybridization of a single impurity model with two distinct conduction bands always adds up constructively, TK∝exp(−constU/(Γ1+Γ2)), we show that this does not have to be the case in lattice models, where, in remarkable contrast, also an low-energy Fermi liquid scale T0∝exp(−constU/(Γ1−Γ2)) can emerge due to quantum interference effects in multi band models, where U denotes the local Coulomb matrix element of the correlated orbitals and Γi the local hybridization strength of band i. At high symmetry points, heavy Fermi liquid formation is suppressed which is associated with a breakdown of the Kondo effect. This results in an asymptotically scale-invariant (i.e., power-law) spectrum of the correlated orbitals ∝|ω|1/3, indicating non-Fermi liquid properties of the quantum critical point, and a small Fermi surface including only the light quasi-particles. This orbital selective Mott phase demonstrates the possibility of metallic local criticality within the general framework of ordinary single site DMFT.
Montagemanipulator für die THT-Bestückung
(2024) Polikarpov, Mikhail; Mehmood, Yousuf; Boiar, Daniel; Deuse, Jochen
In diesem Beitrag wird die Anwendung des parallelkinematischen Manipulators Hexaglide in der THT-Bestückung untersucht. Kostengünstige optische und taktile Sensoren ermöglichen präzises Referenzieren und Einstecken von Bauteilen. Eine kraft- und bildgeregelte heuristische Steuerungsstrategie sowie Reinforcement Learning wurden erprobt und die Tauglichkeit des Hexaglide für die Bestückung wurde experimentell gezeigt.
Digitale Inhalte in physischen Prozessen verankern
(2024) Hönemann, Kay; Konopka, Björn; Brandt, Philipp; Wiesche, Manuel
In diesem Beitrag wird ein Konzept für ein Augmented Reality (AR) Entwicklungstool vorgestellt, das es Nicht-Entwicklern aus der Industrie ermöglicht, eigenständig AR-Anleitungen zu erstellen und die physische Umgebung mit digitalen Inhalten anzureichern. In einer Feldstudie mit 15 Expert*innen aus der Industrie wurde die Praxistauglichkeit, die Nutzerakzeptanz und die entstehende Arbeitsbelastung ermittelt. Als Ergebnis wurden Designempfehlungen erarbeitet, die als Blaupause für die Entwicklung ähnlicher Tools dienen.