Publications associées à Learning Robustly Safe Output Feedback Controllers from Noisy Data with Performance Guarantees

Publications associées (28)

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

Alireza Karimi, Nathan Russell Powell, Mert Eyuboglu

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

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

Alireza Karimi, Mert Eyuboglu

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

Frequency domain data-driven robust and optimal control

Philippe Louis Schuchert

The goal of this thesis is to propose pragmatic solutions to real challenges faced in the industry. The scope of this thesis encompasses two subjects: frequency-based structured controller synthesis for linear time-invariant (LTI) systems on one side, and ...

EPFL2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Data-driven Methods for Control: from Linear to Lifting

Yingzhao Lian

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 ...

EPFL2023

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

Data-driven IQC-Based Robust Control Design for Hybrid Micro-disturbance Isolation Platform

Alireza Karimi, Vaibhav Gupta, Elias Sebastian Klauser

A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approac ...

IEEE2023

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

Experimental Validation of Model-less Robust Voltage Control using Measurement-based Estimated Voltage Sensitivity Coefficients

Mario Paolone, Rahul Kumar Gupta

Increasing adoption of smart meters and phasor measurement units (PMUs) in power distribution networks are enabling the adoption of data-driven/model-less control schemes to mitigate grid issues such as over/under voltages and power-flow congestions. Howev ...

IEEE2023

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

Data-enabled Predictive Control for Empty Vehicle Rebalancing

Nikolaos Geroliminis, Giancarlo Ferrari Trecate, Pengbo Zhu

A critical operational challenge in Mobility-on-demand systems is the problem of imbalance between vehicle supply and passenger demand. However, conventional model-based methods require accurate parametric system models with complex nonlinear dynamics that ...

IEEE2023

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

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

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

Learning dynamical systems with bifurcations

Aude Billard, Farshad Khadivar, Ilaria Lauzana

Trajectory planning through dynamical systems (DS) provides robust control for robots and has found numerous applications from locomotion to manipulation. However, to date, DS for controlling rhythmic patterns are distinct from DS used to control point to ...

Elsevier2021

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

Review of control strategies for lower-limb exoskeletons to assist gait

Auke Ijspeert, Mohamed Bouri, Romain Pierre François Baud, Ali Reza Manzoori

Background Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user. Met ...

BioMed Central2021

Model-Free Iterative Learning Control With Nonrepetitive Trajectories for Second-Order MIMO Nonlinear Systems-Application to a Delta Robot

Mohamed Bouri

A model-free iterative learning control strategy (ILC) in nonrepetitive trajectories, applied to robotic manipulators is presented in this article. The development of this ILC controller is derived in general case for second-order nonlinear multi-input mul ...

2021

Automatic locking of a parametrically resonating, base-excited, nonlinear beam

Amit Yedidia Dolev

Described is a closed-loop control scheme capable of stabilizing a parametrically excited nonlinear structure in several vibration modes. By setting the relative phase between the spatially filtered response and the excitation, the open-loop unstable solut ...

SPRINGER2021

From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues

Aude Billard, José Santos-Victor, Nuno Ricardo Ferreira Duarte, Konstantinos Chatzilygeroudis

Humans manage to communicate action intentions in a non-verbal way, through body posture and movement. We start from this observation to investigate how a robot can decode a human's non-verbal cues during the manipulation of an object, with specific physic ...

IEEE2020