Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Perceptual control theory

Publications associées (29)

Butterfly effects in perceptual development: A review of the 'adaptive initial degradation' hypothesis

Lukas Vogelsang

Human perceptual development evolves in a stereotyped fashion, with initially limited perceptual capabilities maturing over the months or years following the commencement of sensory experience into robust proficiencies. This review focuses on the functiona ...

Academic Press Inc Elsevier Science2024

Using Negative Control Populations to Assess Unmeasured Confounding and Direct Effects

Mats Julius Stensrud

Sometimes treatment effects are absent in a subgroup of the population. For example, penicillin has no effect on severe symptoms in individuals infected by resistant Staphylococcus aureus, and codeine has no effect on pain in individuals with certain polym ...

Lippincott Williams & Wilkins2024

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

Alireza Karimi, Philippe Louis Schuchert

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

Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: An application to the Italian scenario

Alfio Quarteroni, Luca Dede', Nicola Parolini

In the context of SARS-CoV-2 pandemic, mathematical modelling has played a funda-mental role for making forecasts, simulating scenarios and evaluating the impact of pre-ventive political, social and pharmaceutical measures. Optimal control theory represent ...

KEAI PUBLISHING LTD2023

Reinforcement learning approach to control an inverted pendulum: A general framework for educational purposes

Jesus Sanchez Rodriguez

Machine learning is often cited as a new paradigm in control theory, but is also often viewed as empirical and less intuitive for students than classical model-based methods. This is particularly the case for reinforcement learning, an approach that does n ...

PUBLIC LIBRARY SCIENCE2023

Specific Gestalt principles cannot explain (un)crowding

Michael Herzog, Oh-Hyeon Choung, Einat Rashal

The standard physiological model has serious problems accounting for many aspects of vision, particularly when stimulus configurations become slightly more complex than the ones classically used, e.g., configurations of Gabors rather than only one or a few ...

2023

Robust optimization of control parameters for WEC arrays using stochastic methods

Tommaso Vanzan

This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...

Journal of Computational Physics2023

A Proximal-Point Lagrangian-Based Parallelizable Nonconvex Solver for Bilinear Model Predictive Control

Colin Neil Jones, Yuning Jiang, Yingzhao Lian

Nonlinear model predictive control (NMPC) has been widely adopted to manipulate bilinear systems with dynamics that include products of the inputs and the states. These systems are ubiquitous in chemical processes, mechanical systems, and quantum physics, ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Learning and optimization of anticipatory feedback controllers for robot manipulation

Hakan Girgin

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

EPFL2023

Self-Exciting Point Processes: Identification and Control

Michael Mark

This thesis addresses theoretical and practical aspects of identification and subsequent control of self-exciting point processes. The main contributions correspond to four separate scientific papers. In the first paper, we address the challenge of robust ...

EPFL2022

Improved Plasma Vertical Position Control on TCV Using Model-Based Optimized Controller Synthesis

Stefano Coda, Federico Alberto Alfredo Felici, Cristian Galperti, Federico Pesamosca

Elongated plasmas lead to improved performance in tokamaks but make the plasma prone to vertical instability, which requires active feedback control, a critical issue for future fusion reactors. Vertical control was optimized for the TCV tokamak by applyin ...

2022

Performance Analysis of Energy Balancing Methods for Matrix Modular Multilevel Converters

Drazen Dujic, Stefan Milovanovic, Philippe Alexandre Bontemps

Modular multilevel converters achieve voltage scalability through the series connection of cells, each with its own capacitance. However, this converter structure using floating energy storage elements increases the control complexity significantly. The vo ...

2022

Perimeter Control and Route Guidance of Multi-Region MFD Systems With Boundary Queues Using Colored Petri Nets

Nikolaos Geroliminis, Anastasios Kouvelas

Perimeter control based on Macroscopic Fundamental Diagram (MFD) aims to meter the number of transferring vehicles at the periphery of the protected urban region in order to obtain the desired number of vehicles in that region. The advantage of perimeter c ...

IEEE Institute of Electrical and Electronics Engineers2022

Motor control: Neural correlates of optimal feedback control theory

Mackenzie Mathis, Steffen Schneider

Recent work is revealing neural correlates of a leading theory of motor control. By linking an elegant series of behavioral experiments with neural inactivation in macaques with computational models, a new study shows that premotor and parietal areas can b ...

CELL PRESS2021

KPC: Learning-Based Model Predictive Control with Deterministic Guarantees

Colin Neil Jones, Yuning Jiang, Emilio Maddalena, Paul Scharnhorst

We propose Kernel Predictive Control (KPC), a learning-based predictive control strategy that enjoys deterministic guarantees of safety. Noise-corrupted samples of the unknown system dynamics are used to learn several models through the formalism of non-pa ...

2021

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Hierarchical Control of Islanded Microgrids with Flexible Structures

Pulkit Nahata

The primary objective of this doctoral thesis is the design and development of hierarchical control schemes for the overall operation and control of Islanded mGs (ImGs) with flexible structuresâ or, with no reference topologies. The control methodologies ...

EPFL2021

Real-time Control of Battery Energy Storage Systems to Provide Ancillary Services Considering Voltage-Dependent Capability of DC-AC Converters

Mario Paolone, Sidi-Rachid Cherkaoui, Antonio Zecchino, Zhao Yuan

Frequency response and voltage support are vital ancillary services for power grids. In this paper, we design and experimentally validate a real-time control framework for battery energy storage systems (BESSs) to provide ancillary services to power grids. ...

2021

Nonlinear Pricing of Shareable Products

Thomas Alois Weber

We consider a durable-goods monopolist who is able to control the collaborative consumption of its goods on an aftermarket by a sharing tariff. Consumers are heterogeneous with respect to their respective need propensities in each period. We show that the ...

2020

Hierarchical Control in Islanded DC Microgrids With Flexible Structures

Giancarlo Ferrari Trecate, Pulkit Nahata

Hierarchical architectures stacking primary, secondary, and tertiary layers are widely employed for the operation and control of islanded dc microgrids (dcmGs) composed of distribution generation units (DGUs), loads, and power lines. However, a comprehensi ...

2020