Publications associées à Least-restrictive robust periodic model predictive control applied to room temperature regulation

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Alireza Karimi, Mert Eyuboglu, Nathan Russell Powell

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

2024

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Melanie Nicole Zeilinger, Danilo Saccani

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

IEEE2023

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

Dynamic pulse scheduling in ASDEX Upgrade: Disruption avoidance and investigation of the H-Mode density limit

Federico Alberto Alfredo Felici, Alessandro Pau, Bernhard Sieglin

Operation of a tokamak device requires the coordinated operation of a multitude of systems. The sequence of operations during a discharge is both too complex and fast for human interaction. A common way of operation is a predefined sequence of operations w ...

2023

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

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

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

Nikolaos Geroliminis, Anastasios Kouvelas, Hui Fu

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

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

Colin Neil Jones, Andrea Alessandretti, Ye Pu, 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

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

Emergence of diauxie as an optimal growth strategy under resource allocation constraints in cellular metabolism

Vassily Hatzimanikatis, Pierre Guy Rémy Salvy

Diauxie, or the sequential consumption of carbohydrates in bacteria such as Escherichia coli, has been hypothesized to be an evolutionary strategy which allows the organism to maximize its instantaneous specific growth-giving the bacterium a competitive ad ...

National Academy of Sciences2021

Robust Learning Model Predictive Control for Periodically Correlated Building Control

Colin Neil Jones, Yingzhao Lian, Jicheng Shi

Accounting for more than 40% of global energy consumption, residential and commercial buildings will be key players in any future green energy systems. To fully exploit their potential while ensuring occupant comfort, a robust control scheme is required to ...

2021

Data-driven methods for building control - A review and promising future directions

Colin Neil Jones, Yingzhao Lian, Emilio Maddalena

A review of the heating, ventilation and air-conditioning control problem for buildings is presented with particular emphasis on its distinguishing features. Next, we not only examine how data-driven algorithms have been exploited to tackle the main challe ...

2020

A hybrid control strategy for force and precise end effector positioning of a twisted string actuator

Jamie Paik, Andres San Millan Rodriguez

We propose a new control approach for the twisted string actuation (TSA) system; a hybrid control scheme consisting of two nested loops, considering the motor angle and the axial force at the clamping point of the actuator as the system outputs. We show th ...

2021

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

Adaptive model predictive control for linear time varying MIMO systems

Vojislav Gligorovski

A robust, adaptive Model Predictive Control (MPC) approach for asymptotically stable, constrained linear time-varying (LTV) systems with multiple inputs and outputs is proposed. The approach consists of two-steps, carried out on-line with a receding horizo ...

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

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

Colin Neil Jones, Yuning Jiang

This paper proposes a parallelizable real-time algorithm for model predictive control (MPC). In contrast to existing distributed and parallel optimization algorithms for linear MPC such as dual decomposition or the alternating direction method of multiplie ...

IEEE2019

Model-based predictive control methods for distributed energy resources in smart grids

Luca Fabietti

This thesis develops optimization-based techniques for the control of distributed energy resources to provide multiple services to the power network. It is divided into three parts. The first part of this thesis focuses on the development of a framework f ...

EPFL2019

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

Nikolaos Geroliminis, Mehmet Yildirimoglu, Isik Ilber Sirmatel

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 ...

2018