Estimation and control under uncertainty with application to power systems

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For robots to operate in unstructured environments, they are required to interact with objects through contact. Those contacts may be used to push objects to the side, deform objects, or manipulate objects in-hand. This thesis addresses the problem of cont ...

Context. Imaging in radio interferometry requires solving an ill-posed noisy inverse problem, for which the most adopted algorithm is the original CLEAN algorithm and its variants. Alternative explicit optimization methods have gained increasing attention, ...

In studies of medical treatments, individuals often experience post-treatment events that predict their future outcomes. In this work, we study how to use initial observations of a recurrent event - a type of post-treatment event - to offer updated treatme ...

Over the last two decades, Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) has been developed as a powerful MR imaging modality that allows estimating non-invasively the microscopic structure of biological tissues by exploiting the natural motion of ...

This thesis aimed to estimate the effect of demographic and biomechanical preoperative variables on total shoulder arthroplasty (TSA) outcomes. To achieve this, various biomechanical variables were calculated using a clinical database comprising normal and ...

This paper focuses on parameter estimation and introduces a new method for lower bounding the Bayesian risk. The method allows for the use of virtually any information measure, including Rényi's α, φ-divergences, and Sibson's α-Mutual Information. The appr ...

This thesis presents a comprehensive theory of information-theoretic measures for characterizing the complexity and higher-order dependence structures of graphs. We introduce multivariate complexity and dependence measures for graphs within the framework o ...

In our study, we investigated the impact of changes in Mode I fracture toughness and stress barriers on fully developed planar, buoyant hydraulic fractures assuming linear elastic hydraulic fracture mechanics. We present scaling-based arguments to predict ...

Dynamic atomic force microscopy (AFM) modes that operate at frequencies far away from the resonance frequency of the cantilever (off-resonance tapping (ORT) modes) can provide high-resolution imaging of a wide range of sample types, including biological sa ...

Kalman and H-infinity filters, the most popular paradigms for linear state estimation, are designed for very specific specific noise and disturbance patterns, which may not appear in practice. State observers based on the minimization of regret measures ar ...

Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between sub ...

This paper presents a distributed shadow dynamic consensus (DSDC) framework to address the generation company (GENCO) strategic bidding problem in the independent system operator (ISO) operation. First, each sub-group is defined according to the communicat ...

The thesis presents methods for controlling and planning distributed energy resources (DERs) in active distribution networks (ADNs). It deals with three main challenges: (i) developing and experimentally validating grid-aware real-time control frameworks, ...

Photovoltaic parks often utilize communication among the different converters to ensure accurate PCC voltage control and disturbance rejection. However, time delays in the communication network can affect the control performance and stability, and need to ...

Estimation and control under uncertainty with application to power systems

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A Stochastic Approach to Contact-rich Manipulation

PolyCLEAN: Atomic optimization for super-resolution imaging and uncertainty estimation in radio interferometry

A positivity robust strategy to study effects of switching treatment

Simulation-based Microstructure Imaging: Towards Realistic White Matter Modeling using Monte Carlo Methods in DW-MRI

Multimodal Prediction Framework for Total Shoulder Arthroplasty Outcomes: Integrating Morphological, Musculoskeletal, Finite Element, and Bayesian Causal Models

Lower Bounds on the Bayesian Risk via Information Measures

An Information-Theoretic Framework for Multiplex Graphs

How Stress Barriers and Fracture Toughness Heterogeneities Arrest Buoyant Hydraulic Fractures

Enhanced feedback performance in off-resonance AFM modes through pulse train sampling

Minimal regret state estimation of time-varying systems

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

Distributed Shadow Dynamic Consensus Optimization Framework for Power Market with Parameterization Bidding Strategy of GENCOs

Methods for Grid-aware Operation and Planning of Active Distribution Networks

Impact of Communication Delays on Voltage Control Accuracy and Stability of a PV Park