Decisions under uncertainty are ubiquitous in control engineering and seek to provide quantitative solutions when complexity or lack of knowledge about the underlying systems require the probabilistic modeling of their components. Such random elements are often dynamic and the designer needs to make inferences about them using a limited amount of data. Furthermore, the data may only reveal partial-state information about the process, which is often corrupted by noise. All these factors hinder the possibility of making accurate inferences about the underlying probabilistic models and their usage for control design.
To address these issues, this PhD project will leverage tools from state estimation and uncertainty quantification to fuse information from both the data and the known system dynamics and provide robust uncertainty descriptions for reliable decisions and control. The goal is to obtain plausible models about the evolving uncertainty from small data sets based on first-principles assumptions like the classes where the unknown distributions of random initial conditions, parameters, and noise elements belong [1, 2]. Specifically, one seeks to build ambiguity sets of probability distributions that contain the evolving true distribution of the data with high probability and exploit them to take reliable control actions.
The approach will combine techniques across control engineering and applied mathematics, including tools from filtering and nonlinear state estimation, optimization, uncertainty quantification, optimal transport, and high-dimensional probability [3, 4]. The developed data-driven inference and control algorithms will be applied to domains like robotics, power systems, and transportation.
Related work and literature:
 D. Boskos, J. Cortés, and S. Martínez, Data-driven ambiguity sets with probabilistic guarantees for dynamic processes, IEEE Transactions on Automatic Control, 66(7), 2021, to appear, (arXiv:1909.11194).
 D. Boskos, J. Cortés, and S. Martínez, High-confidence data-driven ambiguity sets for time-varying linear systems, 2021, (arXiv:2102.01142).
 F. Santambrogio, Optimal transport for applied mathematicians, Birkäuser, NY, 2015.
 R. Vershynin, High-dimensional probability: An introduction with applications in data science, Cambridge university press, 2018.
The department Delft Center for Systems and Control (DCSC) of the faculty Mechanical, Maritime and Materials Engineering, coordinates the education and research activities in systems and control at Delft University of Technology. The Centers' research mission is to conduct fundamental research in systems dynamics and control, involving dynamic modelling, advanced control theory, optimisation and signal analysis. The research is motivated by advanced technology development in physical imaging systems, renewable energy, robotics and transportation systems.
Ph D Position Track & Trace Of Medical Instruments, Delft University of Technology (TU Delft), Netherlands, 11 days ago
Surgical instrument tracking systems promote patient safety and provide smart alerts when assets require any kind of checkups or maintenance. They deliver information and prevent unnecessary costl...
Three Vacant Positions For Fully Employed University Asisstant’s At The Chair Of Cyber Physical ... (# Of Pos: 3), Personalabteilung der Montanuniversität Leoben, Austria, 11 days ago
Three vacant positions for fully employed University Asisstant’s at the Chair of Cyber-Physical-Systems on the Department of Product Engineering at the earliest possible date or beginning on 15th ...
Ph D & Postdoc Positions In Causal Inference And Machine Learning , Technical University of Munich, Germany, about 15 hours ago
19.05.2021, Wissenschaftliches Personal If you are interested in application-inspired methodology, such as uncertainty, missingness, causal effect, robust inference, or reliable machine learning, ...
Ph D In Automatic Control: Optimized Production Of Biohydrogen By Microalgae In Solar Conditions, L2S - CNRS - CentraleSupelec - Université Paris-Saclay, Suriname, 26 days ago
Description: -------------------- Within the framework of the challenge relating to the energy transition, the valorization of biomass for the production of a biofuel, replacing fossil fuels, repr...
Ph D Studentship – Evaluating Zero Carbon Propulsion Systems For Future Aircraft, Trinity College, Ireland, 23 days ago
Aviation supports 12 million jobs and contributes €700 billion to European GDP. Ireland is a global player in the aviation sector, being home to Europe’s largest airline and the worldwide hub of t...
Ph D Fellow Or Postdoc In Explainable Artificial Intelligence, NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU, Europe, 4 days ago
About the position The Norwegian Open AI Lab and Data and Artificial Intelligence group currently has two vacancies in the field of Explainable Artificial Intelligence (XAI). The positions are pa...