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A Time Splitting Based Real-Time Iteration Scheme for Nonlinear MPC

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Publications associées (39)

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Training Efficient Controllers via Analytic Policy Gradient

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Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

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In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

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Achieving Optimal Performance With Data-Driven Frequency-Based Control Synthesis Methods

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Frequency Response Function (FRF)-based control synthesis methods for Linear Time-Invariant (LTI) systems have been widely used in control theory and industry. Recently, there has been renewed interest in these methods, employing numerical optimization too ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Toward Band n78 Shear Bulk Acoustic Resonators Using Crystalline Y-Cut Lithium Niobate Films With Spurious Suppression

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This work presents the study of suspended Y-cut Lithium Niobate shear bulk acoustic resonators for wide band filter applications in the frequency range of 3.5-4.5GHz. The resonators consist of a Lithium Niobate film with Aluminum top interdigitated electro ...

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Reinforcement Learning for Joint Design and Control of Battery-PV Systems

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The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

2023

High Resolution Light-Based 3D Printing Of Cell-Laden Bio Constructs

Christophe Moser, Damien Claude-Marie Loterie, Paul Delrot, Jorge Andres Madrid Wolff, Antoine Vincent Boniface

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C-shells: Deployable Gridshells with Curved Beams

Mark Pauly, Francis Julian Panetta, Yingying Ren, Quentin Christian Becker, Seiichi Eduardo Suzuki Erazo, Davide Pellis

We introduce a computational pipeline for simulating and designing C-shells, a new class of planar-to-spatial deployable linkage structures. A C-shell is composed of curved flexible beams connected at rotational joints that can be assembled in a stress-fre ...

Association for Computing Machinery (ACM)2023

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Ali Garjani

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

IEEE COMPUTER SOC2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Output regulation via trajectory tracking for chemical reactors with jacket dynamics

Dominique Bonvin

This work deals with a control strategy to regulate homogeneous reaction systems in reactors equipped with a cooling jacket. The reaction system is expressed in terms of vessel extents and viewed as a single-input (the inlet coolant temperature), two-outpu ...

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Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

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This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...

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The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...

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Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

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This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

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In this work, we propose an analytical model for the intrinsic transcapacitances in ultra-thin gate-all-around junctionless nanowire field effect transistors in the presence of confined energy states of electrons. The validity of the developed model is con ...

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Homothetic Tube Model Predictive Control With Multi-Step Predictors

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We present a robust model predictive control (MPC) framework for linear systems facing bounded parametric uncertainty and bounded disturbances. Our approach deviates from standard MPC formulations by integrating multi-step predictors, which provide reduced ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Thermo-hydro-mechanical behavior of energy barrettes: Field experiments and numerical simulations

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Over the past two decades, the thermo-hydro-mechanical behavior of earth-contact structures such as piles, walls, slabs, and tunnels, which simultaneously provide structural support and energy supply, has been studied through various field experiments and ...

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Self-sustained dynamics and forced resonant oscillations in flows: cross-junction jets and sloshing liquids

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In engineering, oscillatory instabilities and resonances are often considered undesirable flow features and measures are taken to avoid them. This may include avoiding certain parametric regions or implementing control and mitigation strategies. However, t ...

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Bayesian Optimization for Chemical Reactions

Philippe Schwaller, Jeff Guo, Bojana Rankovic

Reaction optimization is challenging and traditionally delegated to domain experts who iteratively pro-pose increasingly optimal experiments. Problematically, the reaction landscape is complex and often requires hundreds of experiments to reach convergence ...

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