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Optimization based control for target estimation and tracking via highly observable trajectories

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As third-party cookie blocking is becoming the norm in mainstream web browsers, advertisers and trackers have started to use first-party cookies for tracking. To understand this phenomenon, we conduct a differential measurement study with versus without th ...

New York2023

Probabilistic Adaptive Control for Robust Behavior Imitation

Sylvain Calinon, Julius Maximilian Jankowski, Hakan Girgin

In the context of learning from demonstration (LfD), trajectory policy representations such as probabilistic movement primitives (ProMPs) allow for rich modeling of demonstrated skills. To reproduce a learned skill with a real robot, a feedback controller ...

IEEE2021

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This paper studies a class of partially observed Linear Quadratic Gaussian (LQG) problems with unknown dynamics. We establish an end-to-end sample complexity bound on learning a robust LQG controller for open-loop stable plants. This is achieved using a ro ...

PMLR2021

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Recent advances in Model Predictive Control (MPC) algorithms and methodologies, combined with the surge of computational power of available embedded platforms, allows the use of real-time optimization-based control of fast mechatronic systems. This paper p ...

2021

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Automated predictions require explanations to be interpretable by humans. Past work used attention and rationale mechanisms to find words that predict the target variable of a document. Often though, they result in a tradeoff between noisy explanations or ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Low-Complexity Optimization-Based Control: Design, Methods and Applications

Ivan Pejcic

Optimization-based controllers are advanced control systems whose mechanism of determining control inputs requires the solution of a mathematical optimization problem. In this thesis, several contributions related to the computational effort required for o ...

EPFL2019

Kernel methods and Model predictive approaches for Learning and Control

Sanket Sanjay Diwale

Data-driven modeling and feedback control play a vital role in several application areas ranging from robotics, control theory, manufacturing to management of assets, financial portfolios and supply chains. Many such problems in one way or another are rela ...

EPFL2019

The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly

Dario Floreano, Stefano Mintchev, Davide Scaramuzza

The recent advances in state estimation, perception, and navigation algorithms have significantly contributed to the ubiquitous use of quadrotors for inspection, mapping, and aerial imaging. To further increase the versatility of quadrotors, recent works i ...

2019

Concept of Variants and Invariants for Reaction Systems, with Application to Estimation, Control and Optimization

Diogo Filipe Mateus Rodrigues

The concept of reaction variants and invariants for lumped reaction systems has been known for several decades. Its applications encompass model identification, data reconciliation, state estimation and control using kinetic models. In this thesis, the con ...

EPFL2018

Coordinated Optimization and Control for Smart Grids

Altug Bitlislioglu

In this thesis, we consider commercial buildings with available heating, ventilation and air conditioning (HVAC) systems, and develop methods to assess and exploit their energy storage and production potential to collectively offer ancillary services to th ...

EPFL2018