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Concept

State-space representation

Related publications (29)

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

Data-driven fixed-structure frequency-based H2 and H∞ controller design

Alireza Karimi, Philippe Louis Schuchert, Vaibhav Gupta

The frequency response data of a generalized system is used to design fixed-structure controllers for the H2 and H∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outpu ...

Elsevier BV2024

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

Alessandro Pau, Federico Alberto Alfredo Felici

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

A Provably Stable Iterative Learning Controller for Continuum Soft Robots

Josephine Anna Eleanor Hughes, Francesco Stella

Fully exploiting soft robots' capabilities requires devising strategies that can accurately control their movements with the limited amount of control sources available. This task is challenging for reasons including the hard-to-model dynamics, the system' ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

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

Data-Driven Unknown-Input Observers and State Estimation

Giancarlo Ferrari Trecate, Mustafa Sahin Turan

Unknown-input observers (UIOs) allow for estimation of the states of an LTI system without knowledge of all inputs. In this letter, we provide a novel data-driven UIO based on behavioral system theory and the result known as Fundamental Lemma proposed by J ...

2022

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti

We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...

IEEE2022

Locally active globally stable dynamical systems: Theory, learning, and experiments

Aude Billard, Nadia Barbara Figueroa Fernandez

State-dependent dynamical systems (DSs) offer adaptivity, reactivity, and robustness to perturbations in motion planning and physical human-robot interaction tasks. Learning DS-based motion plans from non-linear reference trajectories is an active research ...

SAGE PUBLICATIONS LTD2022

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

Advanced methods for Brillouin based distributed optical fiber sensors

Simon Adrien Zaslawski

After more than thirty years of continuous research and development, the performances of conventional Brillouin based distributed optical fiber sensors (DOFS) are now peaking, as they are facing fundamental barriers that restrict the power of the light inj ...

EPFL2021

Topological Linear System Identification via Moderate Deviations Theory

Daniel Kuhn, Wouter Jongeneel, Tobias Sutter

Two dynamical systems are topologically equivalent when their phase-portraits can be morphed into each other by a homeomorphic coordinate transformation on the state space. The induced equivalence classes capture qualitative properties such as stability or ...

2022

Robust Localization for Multi-robot Formations: An Experimental Evaluation of an Extended GM-PHD Filter

Alcherio Martinoli, Alicja Barbara Roelofsen

This paper presents a thorough experimental evaluation of an extended Gaussian Mixture Probability Hypothesis Density filter which is able to provide state estimates for the maintenance of a multirobot formation, even when the communication fails and the t ...

Springer Nature2021

Predictors and predictands of linear response in spatially extended systems

Umberto Maria Tomasini

The goal of response theory, in each of its many statistical mechanical formulations, is to predict the perturbed response of a system from the knowledge of the unperturbed state and of the applied perturbation. A new recent angle on the problem focuses on ...

SPRINGER HEIDELBERG2021

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

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Lucas Cesar Eduardo Cassano

This article develops a fully decentralized multiagent algorithm for policy evaluation. The proposed scheme can be applied to two distinct scenarios. In the first scenario, a collection of agents have distinct datasets gathered by following different behav ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Invariant states in inclined layer convection. Part 2. Bifurcations and connections between branches of invariant states

Tobias Schneider, Florian Reetz

Convection in a layer inclined against gravity is a thermally driven non-equilibrium system, in which both buoyancy and shear forces drive spatio-temporally complex flows. As a function of the strength of thermal driving and the angle of inclination, a mul ...

Cambridge University Press2020

Invariant states in inclined layer convection. Part 1. Temporal transitions along dynamical connections between invariant states

Tobias Schneider, Florian Reetz

Thermal convection in an inclined layer between two parallel walls kept at different fixed temperatures is studied for fixed Prandtl number . Depending on the angle of inclination and the imposed temperature difference, the flow exhibits a large variety of ...

Cambridge University Press2020

Simultaneous unwrapping and low pass filtering of continuous phase maps based on autoregressive phase model and wrapped Kalman filtering

Pramod Rastogi, Rishikesh Dilip Kulkarni

We propose a simultaneous noise filtering and phase unwrapping algorithm. Spatial evolution of phase is modeled as an autoregressive Gaussian Markov random field. Accordingly, phase value at a pixel is related to phase values at surrounding pixels in a pro ...

2020

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

Daniel Maria Busiello

We consider a general discrete state-space system with both unidirectional and bidirectional links. In contrast to bidirectional links, there is no reverse transition along the unidirectional links Herein, we first compute the statistical length and the th ...

2020

Modeling time-varying brain networks with a self-tuning optimized Kalman filter

Gijs Plomp, David Pascucci

Brain networks are complex dynamical systems in which directed interactions between different areas evolve at the sub-second scale of sensory, cognitive and motor processes. Due to the highly non-stationary nature of neural signals and their unknown noise ...

2020