Concept

Perceptual control theory

Related publications (131)

Kernel methods and Model predictive approaches for Learning and Control

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

Unified Approach to Convex Robust Distributed Control Given Arbitrary Information Structures

Maryam Kamgarpour, Luca Furieri

We consider the problem of computing optimal linear control policies for linear systems in finite-horizon. The states and the inputs are required to remain inside prespecified safety sets at all times despite unknown disturbances. In this technical note, w ...

2019

A data-driven approach to model-reference control with applications to particle accelerator power converters

Alireza Karimi, Achille Nicoletti, Michele Martino

A new model-reference data-driven approach is presented which uses the frequency response data of a system in order to avoid the problem of unmodeled dynamics associated with low-order parametric models. It is shown that a convex optimization problem can b ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Optimal Control of Part Load Vortex Rope in Francis Turbines

François Avellan, François Gallaire, Simon Pasche

The mitigation of the precessing vortex core developing in the draft tube of Francis turbines operating under part load conditions is crucial to increase the operation flexibility of these hydraulic machines to balance the massive power production of inter ...

ASME2019

Runaway electron beam stability and decay in COMPASS

Joan Decker, Gergely Papp

This paper presents two scenarios used for generation of a runaway electron (RE) beam in the COMPASS tokamak with a focus on the decay phase and control of the beam. The first scenario consists of massive gas injection of argon into the current ramp-up pha ...

IOP PUBLISHING LTD2019

Control Theory Concepts for Modeling Uncertainty in Enzyme Kinetics of Biochemical Networks

Vassily Hatzimanikatis, Ljubisa Miskovic, Georgios Savoglidis, Milenko Tokic

Analysis of the dynamic and steady-state properties of biochemical networks hinges on information about the parameters of enzyme kinetics. The lack of experimental data characterizing enzyme activities and kinetics along with the associated uncertainties i ...

2019

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

Maryam Kamgarpour, Luca Furieri

This letter proposes a novel input-output parametrization of the set of internally stabilizing output-feedback controllers for linear time invariant (LTI) systems. Our underlying idea is to directly treat the closed-loop transfer matrices from disturbances ...

2019

Deep Drone Racing: From Simulation to Reality with Domain Randomization

Davide Scaramuzza

Dynamically changing environments, unreliable state estimation, and operation under severe resource constraints are fundamental challenges for robotics, which still limit the deployment of small autonomous drones. We address these challenges in the context ...

2019

Hierarchical control of heterogeneous large-scale urban road networks via path assignment and regional route guidance

Nikolaos Geroliminis, Isik Ilber Sirmatel, Mehmet Yildirimoglu

High level of detail renders microscopic traffic models impractical for control purposes and local control schemes cannot coordinate actions over large scale heterogeneously congested urban networks. Developing efficient models and control methods for larg ...

PERGAMON-ELSEVIER SCIENCE LTD2018

Robust Distributed Control Beyond Quadratic Invariance

Maryam Kamgarpour, Luca Furieri

The problem of robust distributed control arises in several large-scale systems, such as transportation networks and power grid systems. In many practical scenarios controllers might not have enough information to make globally optimal decisions in a tract ...

IEEE2018

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