Publication

Shape design in aorto-coronaric bypass anastomoses using perturbation theory

Publications associées (24)

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...

2024

Accurate and agile flight with winged drones

Valentin Wüest

Drones hold promise to assist in civilian tasks. To realize this application, future drones must operate within large cities, covering large distances while navigating within cluttered urban landscapes. The increased efficiency of winged drones over rotary ...

EPFL2024

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

Optimal Thrust Vector Control of an Electric Small-Scale Rocket Prototype

Colin Neil Jones, Petr Listov, Roland Schwan

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 ...

IEEE2022

Reference tracking stochastic model predictive control over unreliable channels and bounded control actions

Colin Neil Jones

A stochastic model predictive control framework over unreliable Bernoulli communication channels, in the presence of unbounded process noise and under bounded control inputs, is presented for tracking a reference signal. The data losses in the control chan ...

2021

Whole Body Model Predictive Control with a Memory of Motion: Experiments on a Torque-Controlled Talos

Sylvain Calinon, Rohan Budhiraja, Teguh Santoso Lembono

This paper presents the first successful experiment implementing whole-body model predictive control with state feedback on a torque-control humanoid robot. We demonstrate that our control scheme is able to do whole-body target tracking, control the balanc ...

IEEE2021

Optimal Linear Controller for Minimizing DC Voltage Oscillations in MMC-Based Offshore Multiterminal HVDC Grids

Luca Furieri, Maryam Kamgarpour

The paper aims at minimizing DC voltage oscillations in offshore multiterminal high-voltage direct current (HVDC) grids based on modular multilevel converters (MMCs). The DC voltage stability is a crucial factor in multiterminal HVDC networks since it is a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Harsh Ambarishkumar Shukla

The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

EPFL2021

PolyMPC: An efficient and extensible tool for real‐time nonlinear model predictive tracking and path following for fast mechatronic systems

Colin Neil Jones, Petr Listov

This paper presents PolyMPC, an open‐source C++ library for pseudospectral‐based real‐time predictive control of nonlinear systems. It provides a necessary background on the computational aspects of the pseudospectral approximation of optimal control probl ...

2020

Shape changes through geometric nonlinear control as a strategy for structural adaptation

Arka Prabhata Reksowardojo

Adaptive structures modify their geometry and internal forces through sensing and mechanical actuation in order to maintain optimal performance under changing actions. Previous work has shown that well-conceived adaptive design strategies achieve substanti ...

EPFL2020

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

Second-order sensitivity in the cylinder wake: Optimal spanwise-periodic wall actuation and wall deformation

François Gallaire, Edouard Boujo, Andrea Fani

Two-dimensional (2D) flows can be controlled efficiently using spanwise "waviness," i.e., a control (e.g., wall blowing and suction or wall deformation) that is periodic in the spanwise direction. This study tackles the global linear stability of 2D flows ...

AMER PHYSICAL SOC2019

Design of Magnetic Bearing Control System Based on Active Disturbance Rejection Theory

Yuanping Xu

At present, most of the magnetic bearing system adopts the classical proportional-integral-derivative (PID) control strategy. However, the external disturbances, system parameter perturbations, and many other uncertain disturbances result in PID controller ...

2019

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

Response of noise-amplifier flows: From linear control to nonlinear jet breakup

Isha Shukla

Among hydrodynamically unstable flows, the amplifier-flows are characterized by their large amplification potential in presence of external noise. Since amplifiers do not have an intrinsic dynamics, a chosen forcing can be applied to eventually control the ...

EPFL2019

Linear-parameter-varying model predictive control for multi-region traffic systems

Nikolaos Geroliminis, Mohammadreza Saeedmanesh, Anastasios Kouvelas

An alternative approach for real-time network-wide traffic control in cities that has recently gained a lot of interest is perimeter flow control. The basic concept of such an approach is to partition heterogeneous cities into a small number of homogeneous ...

2019

Manifold Learning and Optimal Control for Obstacle Avoidance in Autonomous Driving

Colin Neil Jones, Sanket Sanjay Diwale

A novel manifold learning approach is presented to incorporate computationally efficient obstacle avoidance constraints in optimal control algorithms. The method presented provides a significant computational benefit by reducing the number of constraints r ...

2019

PDE-Constrained Optimal Control Problems with Uncertain Parameters using SAGA

Fabio Nobile, Matthieu Claude Martin

We consider an optimal control problem (OCP) for a partial differential equation (PDE) with random coefficients. The optimal control function is a deterministic, distributed forcing term that minimizes an expected quadratic regularized loss functional. For ...

2021

Dynamics and Optimal Control of Self-Sustained Instabilities in Laminar and Turbulent Swirling Flows: Application to the Part Load Vortex Rope in Francis Turbines

Simon Pasche

In 2050, the European commission plans to achieve actual energetic transition, which contributes in meeting the climate change challenges by moving away from the fossil fuels and by developing a competitive low-carbon economy. As a consequence, a foreseeab ...

EPFL2018

Data-driven Demand Response Modeling and Control of Buildings with Gaussian Processes

Colin Neil Jones, Xuan Truong Nghiem

This paper presents an approach to provide demand response services with buildings. Each building receives a normalized signal that tells it to increase or decrease its power demand, and the building is free to implement any suitable strategy to follow the ...

2017