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23 results on '"IEEE Control Systems Society"'

3. On minimal LPV state-space representations in innovation form: an algebraic characterization

Author

Rouphael, Elie, Mihaly, Petreczky, Belkoura, Lotfi, Non-Asymptotic estimation for online systems (NON-A-POST), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), IEEE Control Systems Society, Society for Industrial and Applied Mathematics, Japanese Society for Instrument and Control Engineers, Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL], Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), and Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)

Subjects
Optimization and Control (math.OC), Computer Science::Systems and Control, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, FOS: Mathematics, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Mathematics - Optimization and Control, [SPI.AUTO]Engineering Sciences [physics]/Automatic, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; In this paper we will propose a definition of the concept of minimal state-space representations in innovation form for LPV. We also present algebraic conditions for a stochastic LPV state-space representation to be minimal in forward innovation form and discuss an algorithm for transforming any stochastic LPV state-space representation to a minimal one in innovation form.

Published
2022
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4. A YOLO-based pest detection system for precision agriculture

Author

Andrea Gasparri, Martina Lippi, Niccolo Bonucci, Stefano Speranza, Mario Contarini, Renzo Fabrizio Carpio, Institute of Electrical and Electronics Engineers., IEEE Robotics and Automation Society., IEEE Control Systems Society., Mediterranean Control Association., Lippi, M., Bonucci, N., Carpio, R. F., Contarini, M., Speranza, S., and Gasparri, A.

Subjects
Software bug, business.industry, Computer science, Histogram, Online processing, Early detection, Artificial intelligence, Precision agriculture, business, Machine learning, computer.software_genre, Convolutional neural network, computer
Abstract

In this work, inspired by the needs of the H2020 European project PANTHEON for the precision farming of hazelnut orchards, we propose a data-driven pest detection system. Indeed, the early detection of pests represents an essential step towards the design of effective crop defense strategies in Precision Agriculture (PA) settings. Among the possible pests, we focus on true bugs as they can heavily compromise hazelnut production. To this aim, we collect a custom dataset in a realistic outdoor environment and train a You Only Look Once (YOLO)-based Convolutional Neural Network (CNN), achieving ≈ 94.5% average precision on a holdout dataset. We extensively evaluate the detector performance by also analyzing the influence of data augmentation techniques and of depth information. We finally deploy it on a NVIDIA Jetson Xavier on which it reaches ≈ 50 fps, enabling online processing on-board of any robotic platform.

Published
2021

5. Distributed Finite-Time Algorithm for a Class of Quadratic Optimization Problems with Time-Varying Linear Constraints

Author

Matteo Santilli, Andrea Gasparri, Gabriele Oliva, IEEE Control Systems Society, Santilli, M., Oliva, G., and Gasparri, A.

Subjects
0209 industrial biotechnology, Class (computer programming), Optimization problem, Observer (quantum physics), Computer science, 020206 networking & telecommunications, 02 engineering and technology, Global optimal, 020901 industrial engineering & automation, Distributed algorithm, 0202 electrical engineering, electronic engineering, information engineering, Trajectory, Quadratic programming, Finite time, Algorithm
Abstract

In this paper we develop a multi-agent distributed algorithm to solve a quadratic programming problem with linear time-varying constraints. In more detail, we first solve the frozen-time optimization problem, providing a necessary and sufficient global optimality condition. Then, based on such condition we develop a continuous-time nonsmooth algorithm that is able to track the time-varying global optimal solution in finite-time. The proposed algorithm requires 2-hop neighborhood information that can be estimated by resorting to a state-of-the art finite-time k-hop distributed observer which can be implemented using only 1-hop information. Numerical results are provided to corroborate the theoretical findings.

Published
2020

6. A Finite-Time Protocol for Distributed Continuous-Time Optimization of Sum of Locally Coupled Strictly Convex Functions

Author

Alessandro Marino, Andrea Gasparri, Matteo Santilli, IEEE Control Systems Society, Santilli, Matteo, Marino, A., and Gasparri, A.

Subjects
0301 basic medicine, 0209 industrial biotechnology, Mathematical optimization, Optimization problem, Computer science, 02 engineering and technology, Observer (special relativity), Network topology, 03 medical and health sciences, 030104 developmental biology, 020901 industrial engineering & automation, Descent direction, Finite time, Gradient descent, Convex function
Abstract

In this paper we study a distributed optimization problem for continuous time multi-agent systems. In our setting, the global objective for the multi-agent system is to minimize the sum of locally coupled strictly convex cost functions. Notably, this class of optimization objectives can be used to encode several important problems such as distributed estimation. For this problem setting, we propose a distributed signed gradient descent algorithm, which relies on local observers to retrieve 2-hop state information that are required to compute the descent direction. Adaptive gains for the local observer are introduced to render the convergence independent from: i) the structure of the network topology and ii) the local gains of the per-agent signed gradient-descent update law. The finite-time convergence of the local observer and of the proposed signed gradient descent method is demonstrated. Numerical simulations involving a distributed weighted least-square (WLS) estimation problem, with the aim of identifying in the context of an advanced water management system for precision-farming the soil thermal properties in a large-scale hazelnut orchard, have been proposed to corroborate the theoretical findings.

Published
2018
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7. Distributed Estimation of Node Centrality with Application to Agreement Problems in Social Networks

Author

Andrea Gasparri, Gabriele Oliva, Eduardo Montijano, IEEE Control Systems Society, Montijano, E., Oliva, G., and Gasparri, A.

Subjects
0209 industrial biotechnology, Theoretical computer science, Social network, business.industry, Generalization, Computer science, Node (networking), Eigenvector centrality, 020206 networking & telecommunications, 02 engineering and technology, Influencer marketing, Graph, Identification (information), 020901 industrial engineering & automation, 0202 electrical engineering, electronic engineering, information engineering, business, Focus (optics), Centrality, Protocol (object-oriented programming)
Abstract

Measures of node centrality that describe the importance of a node within a network are crucial for understanding the behavior of social networks and graphs. In this paper, we address the problem of distributed node centrality identification. In particular, we focus our attention on alpha-centrality, which can be seen as a generalization of eigenvector centrality, particularly suitable for graphs with asymmetric interactions. In this setting, our contribution is twofold: first we derive a distributed protocol where agents can locally compute their alpha-centrality index by means of local interactions; then we propose a novel consensus-algorithm running in parallel to the alpha-centrality estimator, which converges towards a weighted average of the initial conditions, where the weights are dictated by the alpha-centrality vector. The proposed algorithm finds application in social networks, where agreement protocols typically place more value on experts and influencers than on the rest of users. Simulations results are provided to corroborate the theoretical findings.

Published
2018
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8. Optimal Redesign of Markov Chains with Prescribed Repulsive Distribution

Author

Andrea Gasparri, Gabriele Oliva, Matteo Santilli, IEEE Control Systems Society, Santilli, M., Gasparri, A., and Oliva, G.

Subjects
0209 industrial biotechnology, Mathematical optimization, 020901 industrial engineering & automation, Optimization problem, Markov chain, Order (exchange), Computer science, 0202 electrical engineering, electronic engineering, information engineering, 020206 networking & telecommunications, 02 engineering and technology, Distribution (differential geometry)
Abstract

Optimization over Markov chains is a popular topic, since Markov chains can be used to model several important systems, such as telecommunications, railways or dams. However, most of the existing literature focuses on steady states and limiting distributions, while in some contexts it might be beneficial to design Markov chains with repulsive distributions, i.e., distributions that, once achieved, cause a large probability transition in the system. This, as typically done in Critical Infrastructure systems, corresponds to having resilient Markov chains that 'spring back' after reaching potentially dangerous or unsafe configurations. In this paper we formulate a problem where we aim at redesigning a Markov chain in order from one side to maximize the repulsiveness of a prescribed distribution and from another side to minimize the redesign effort. In more detail, we formulate the problem as an optimization problem, and we provide a necessary and sufficient local optimality condition and a sufficient global optimality condition. We conclude the paper with simulations aimed at numerically demonstrating the theoretical findings in the paper.

Published
2018
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9. A Distributed Swarm Aggregation Algorithm for Bar Shaped Multi-Agent Systems

Author

Giovanni Ulivi, Emanuele Garone, Letizia Di Giulio, Renzo Fabrizio Carpio, Andrea Gasparri, IEEE Control Systems Society, Carpio, RENZO FABRIZIO, Di Giulio, L., Garone, E., Ulivi, G., and Gasparri, A.

Subjects
0209 industrial biotechnology, Robot kinematics, Computer science, Multi-agent system, Distributed computing, Swarm behaviour, Ranging, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, 020901 industrial engineering & automation, 010201 computation theory & mathematics, State space, Robot, Precision agriculture, Collision avoidance
Abstract

In this work we consider a swarm of agents shaped as bars with a certain orientation in the state space. Members of the swarm have to reach an aggregate state, while guaranteeing the collision avoidance and possibly achieving an angular consensus. By relying on a segment-to-segment distance definition, we propose a control law, which guides the agents towards this goal. A theoretical analysis of the proposed control scheme along with simulations and experimental results is provided. The proposed framework can be used to model several application scenarios ranging from collaborative transportation to precision farming, where each agent may represent either a large robot or a group of robots intent to carry bar-like shaped loads. Representative examples include: a fleet of robot-teams performing a collaborative object transportation task in an automated logistic setting, or a fleet of autonomous tractors each carrying a large atomizer to spray chemical products for pest and disease control in a precision farming setting.

Published
2018
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10. Trust in multi-agent networks: From self-centered to team-oriented

Author

Tina Setter, Magnus Egerstedt, Andrea Gasparri, IEEE Control Systems Society, Setter, Tina, Gasparri, Andrea, and Egerstedt, Magnus

Subjects
0209 industrial biotechnology, Engineering, Knowledge management, business.industry, Multi-agent system, 05 social sciences, 02 engineering and technology, 050105 experimental psychology, Electronic mail, 020901 industrial engineering & automation, Work (electrical), If and only if, Order (exchange), 0501 psychology and cognitive sciences, Interaction dynamics, Computational trust, Electrical and Electronic Engineering, business
Abstract

In this work, we incorporate trust into the interaction dynamics for multi-agent systems in order to analyze the effects of trust on human-robot teams. We extend previous work by moving away from a 'self-centered' trust model and introduce a so-called 'team-oriented' trust model in which each agent increases its trust for its neighbors only if they are collectively contributing to the team's overall goal. The coupling of the trust dynamics and the agents' state dynamics is shown to give rise to an intricate relationship that has the potential to make the team's performance deteriorate under certain circumstances. We derive conditions under which the multi-agent system is guaranteed to achieve a collective objective and provide simulations to corroborate the theoretical findings.

Published
2017
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11. Modeling and estimation of the pollutants emissions in the Compression Ignition diesel engine

Author

Nelson Gruel, Dominique, Nelson-Gruel, D., Chamaillard, Yann, Aljarbouh, A., Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME), Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), F2ME, Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique (PRISME), Université d'Orléans (UO)-Ecole Nationale Supérieure d'Ingénieurs de Bourges (ENSI Bourges)-Université d'Orléans (UO)-Ecole Nationale Supérieure d'Ingénieurs de Bourges (ENSI Bourges), and IEEE Control Systems Society

Subjects
Engineering, Nitrogen, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], Combustion, [PHYS.MECA.GEME]Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph], Fuels, Diesel engine, 7. Clean energy, Automotive engineering, [SPI.AUTO]Engineering Sciences [physics]/Automatic, law.invention, Diesel fuel, Mathematical model, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, law, Analytical models, ComputingMilieux_MISCELLANEOUS, NOx, Pollutant, business.industry, Diesel engines, Homogeneous charge compression ignition, Particulates, Ignition system, Atmospheric modeling, 13. Climate action, [PHYS.MECA.THER]Physics [physics]/Mechanics [physics]/Thermics [physics.class-ph], business
Abstract

International audience; Legislation concerning the pollutant emissions of diesel passenger cars is becoming increasingly restrictive, especially for nitrogen oxide (NOx) and particulate matter (PM). A methodology that combined physical approach and a dynamic output feedback based observer for the modelling and estimation of the pollutant emissions in diesel engines is thus proposed. A grey box control-oriented model of NOx emissions is developed; this model was designed based on a deep analysis of the crank-angle discrete combustion process of the test-bench diesel engine. This model will be used to help the understanding of the thermal NOx emission formation process. It provides the basics for the further development of the diesel engine emissions control-oriented models, but it couldn't be used to predict real-time pollutant emissions on a vehicle. The model is calibrated by experimental measurements and a complete cylinder pressure and temperature analysis. Then, to solve the vehicle integration problem (real-time calculation problem) this model and a linear model of the diesel engine were used to develop an dynamic observer to estimate the quantities of particulate matter.

Published
2016
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12. A real-time inverse-based hysteresis compensation with adaptation

Author

Jakub Dokoupil, Gildas Besancon, Lukasz Ryba, Alina Voda, GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), GIPSA - Systèmes linéaires et robustesse (GIPSA-SLR), Brno University of Technology [Brno] (BUT), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), IEEE Control Systems Society (CSS), and Ryba, Lukasz

Subjects
0209 industrial biotechnology, 020208 electrical & electronic engineering, Inverse, 02 engineering and technology, Minimax, Compensation (engineering), [SPI.AUTO]Engineering Sciences [physics]/Automatic, [SPI.AUTO] Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, Polynomial and rational function modeling, Hysteresis (economics), Control theory, Adaptive estimator, Parametric model, 0202 electrical engineering, electronic engineering, information engineering, CDC, Mathematics, Parametric statistics
Abstract

International audience; This paper presents a novel approach for compensation of hysteresis present for example in piezoelectric actuators. This adverse phenomenon limits seriously their accuracy, especially for large range positioning. The advantage of the proposed method is that it only requires the parametric description of the hysteresis model and does not require modeling its inverse directly. Instead, a combination of Newton and bisection algorithms is incorporated to solve for proper compensation input on-line. A simple polynomial model is chosen to approximate the hysteresis curve. The novelty of the proposed method is based on the adaptation of such a parametric model in real-time. In this way, one avoids modeling both ascending and descending branches of hysteresis separately and/or for different amplitude of the input. In order to track time varying parameters an adaptive estimator with stabilized exponential forgetting in a Bayesian framework is proposed. The optimal value of the forgetting factor is found by solving a maximin problem containing the Kullback-Leibler divergences. The method is validated experimentally on piezoelectric actuator in horizontal axis of some STM-like lab-made nanopositioning platform.

Published
2015

13. Minimal time control of the two tanks gradostat model under cascade inputs constraint

Author

Alain Rapaport, Térence Bayen, Matthieu Sebbah, Modelling and Optimisation of the Dynamics of Ecosystems with MICro-organisme ( MODEMIC ), Inria Sophia Antipolis - Méditerranée ( CRISAM ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie ( MISTEA ), Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ) -Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie ( MISTEA ), Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Institut de Mathématiques et de Modélisation de Montpellier ( I3M ), Université Montpellier 2 - Sciences et Techniques ( UM2 ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Inria Chile ( CIRIC ), Universidad Diego Portales [Santiago] ( UDP ) -Universidad de la frontera [Chile]-Universidad de Concepción [Chile]-Pontificia Universidad Católica de Chile-Institut National de Recherche en Informatique et en Automatique ( Inria ) -Pontificia Universidad Católica de Valparaíso-Universidad Adolfo Ibáñez [Santiago]-Universidad de Santiago de Chile [Santiago] ( USACH ) -Universidad Tecnica Federico Santa Maria [Valparaiso] ( UTFSM ) -Universidad de Valparaiso [Chile], INRIA Associated team DYMECOS and BIONATURE project, CIRIC, Inria Chile, INRIA Associated team with Chile: DYMECOS, Modelling and Optimisation of the Dynamics of Ecosystems with MICro-organisme (MODEMIC), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Institut de Mathématiques et de Modélisation de Montpellier (I3M), Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Inria Chile (CIRIC), Universidad Diego Portales [Santiago] (UDP)-Universidad de la frontera [Chile]-Universidad de Concepción [Chile]-Pontificia Universidad Católica de Chile (UC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Pontificia Universidad Católica de Valparaíso (PUCV)-Universidad Adolfo Ibáñez [Santiago]-Universidad de Valparaiso [Chile]-Universidad Tecnica Federico Santa Maria [Valparaiso] (UTFSM)-Universidad de Santiago de Chile [Santiago] (USACH), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM), Inria Chile, Universidad de Valparaiso [Chile]-Universidad Tecnica Federico Santa Maria [Valparaiso] (UTFSM)-Universidad Adolfo Ibáñez [Santiago]-Pontificia Universidad Católica de Valparaíso (PUCV)-Institut National de Recherche en Informatique et en Automatique (Inria)-Pontificia Universidad Católica de Chile (UC)-Universidad de Concepción [Chile]-Universidad de la frontera [Chile]-Universidad Diego Portales [Santiago] (UDP), Université de Strasbourg (Unistra). France, FRA. IEEE Control Systems Society., Institut Montpelliérain Alexander Grothendieck ( IMAG ), Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), INRIA Sophia Antipolis, Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Département de Mathématiques (IREM), Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Universidad Diego Portales [Santiago] (UDP)-Universidad de la frontera [Chile]-Pontificia Universidad Católica de Chile (UC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Pontificia Universidad Católica de Valparaíso (PUCV)-Universidad Adolfo Ibáñez [Santiago]-Universidad de Valparaiso [Chile]-Universidad Tecnica Federico Santa Maria [Valparaiso] (UTFSM)-Universidad de Concepción - University of Concepcion [Chile]

Subjects
chemostat model, [ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC], minimal time problem, Mathematical optimization, semi-permeability, Series (mathematics), Singular point of a curve, Optimal control, optimal synthesis, Domain (mathematical analysis), [SPI.AUTO]Engineering Sciences [physics]/Automatic, Controllability, Constraint (information theory), optimal control, non-linear controllability, Cascade, Control theory, Position (vector), gradostat model, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Pontryagin Maximum Principle, ComputingMilieux_MISCELLANEOUS, Mathematics
Abstract

hal-01086152; International audience; We study the minimum time control problem of a series of two interconnected chemostats under the input constraint u(2)

Published
2014
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14. Minimal time problem for a chemostat model with growth rate of Haldane type

Author

Jérôme Harmand, Térence Bayen, Département de Mathématiques (IREM), Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut National de Recherche en Informatique et en Automatique (Inria), Université de Strasbourg (Unistra). France, FRA. IEEE Control Systems Society., Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Institut de Mathématiques et de Modélisation de Montpellier (I3M), Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Modelling and Optimisation of the Dynamics of Ecosystems with MICro-organisme (MODEMIC), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Centre National de la Recherche Scientifique (CNRS)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie ( MISTEA ), Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Institut de Mathématiques et de Modélisation de Montpellier ( I3M ), Université Montpellier 2 - Sciences et Techniques ( UM2 ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Modelling and Optimisation of the Dynamics of Ecosystems with MICro-organisme ( MODEMIC ), Inria Sophia Antipolis - Méditerranée ( CRISAM ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie ( MISTEA ), Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ) -Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Laboratoire de Biotechnologie de l'Environnement [Narbonne] ( LBE ), and Institut national de la recherche agronomique [Montpellier] ( INRA Montpellier ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro )

Subjects
[ MATH ] Mathematics [math], 0209 industrial biotechnology, Mathematical optimization, Work (thermodynamics), 021103 operations research, Feedback control, 0211 other engineering and technologies, biological systems, 02 engineering and technology, Chemostat, Type (model theory), Optimal control, Separation principle, Pontryagin's minimum principle, [SPI.AUTO]Engineering Sciences [physics]/Automatic, optimal control, 020901 industrial engineering & automation, Growth rate, [MATH]Mathematics [math], Mathematics
Abstract

hal-01090654; International audience; In this work, we consider an optimal control problem for a system describing a chemostat with one species and one substrate. Our objective is to find an optimal feedback control in order to reach in minimal time a target point. This problem has been addressed in the case where the growth rate is of Monod type. Here, we suppose that the growth rate is of Haldane type, which implies the existence of a singular arc. Thanks to Pontryagin maximum principle, we provide an optimal synthesis (optimal feeding strategy) of the problem.

Published
2014
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15. Uncertainty Quantification for Stochastic Nonlinear Systems using Perron-Frobenius Operator and Karhunen-Lo'eve Expansion

Author

Dutta, Parikshit, Halder, Abhishek, Bhattacharya, Raktim, Sustainability transition, environment, economy and local policy (STEEP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Department of Aerospace Engineering [College Station] (TAMU), Texas A&M University [College Station], IEEE Control Systems Society, Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.7: Probabilistic algorithms (including Monte Carlo), [STAT.AP]Statistics [stat]/Applications [stat.AP], [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.15: Stochastic processes
Abstract

International audience; In this paper, a methodology for propagation of uncertainty in stochastic nonlinear dynamical systems is investigated. The process noise is approximated using Karhunen-Lo'eve (KL) expansion. Perron-Frobenius (PF) operator is used to predict the evolution of uncertainty. A multivariate Kolmogorov-Smirnov test is used to verify the proposed framework. The method is applied to predict uncertainty evolution in a Duffing oscillator and a Vanderpol's oscillator. It is observed that the solution of the approximated stochastic dynamics converges to the true solution in distribution. Finally, the proposed methodology is combined with Bayesian inference to estimate states of a nonlinear dynamical system, and its performance is compared with particle filter. The proposed estimator was found to be computationally superior than the particle filter.

Published
2012
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16. Towards a systematic approach to reduce complex bioprocess models - Application to the ADM1

Author

Elena Ficara, Jérôme Harmand, Brahim Cherki, Sonia Hassam, Université Abou Bekr Belkaid Tlemcen, DIIAR, Environmental section, Politecnico di Milano [Milan] (POLIMI), Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Modelling and Optimisation of the Dynamics of Ecosystems with MICro-organisme (MODEMIC), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), IEEE Control Systems Society. FRA., Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
Mathematical optimization, Reduced model, Reduction method, [SDV]Life Sciences [q-bio], Slow dynamics, 02 engineering and technology, 010501 environmental sciences, 01 natural sciences, Steady state, Reduction (complexity), Time-scales, Matrix (mathematics), Bioprocess, 0105 earth and related environmental sciences, Mathematics, Anaerobic digestion model, Bioprocesses, Complex model, Gramians, Homotopies, Input-output, Mathematical reduction, Homotopy, 021001 nanoscience & nanotechnology, Transformation (function), Matrix algebra, [SDE]Environmental Sciences, 0210 nano-technology
Abstract

International audience; A mathematical reduction method named Homotopy is applied to the Anaerobic Digestion Model No. 1 or ADM1, cf. (Batstone et al., 2002), a complex model of bioprocess describing the anaerobic digestion. Because we are interested in what happens on small timescales, the proposed method neglects the slow dynamics keeping only the fastest ones in using the technique of eigenvalue-state association. This transformation is described by the Homotopy matrix H. Simulations show that the reduced model behaves globally like the initial model at steady states. This approach is confronted with the reduction method using balancing of empirical gramians, an approach that ensures the same input-output behaviour of the reduced model with regard to the original one.

Published
2012

17. Particle filtering for the chemostat

Author

Jérôme Harmand, Brahim Cherki, Fabien Campillo, Boumediene Benyahia, Laboratoire d'Automatique de Tlemcen (LAT), Université Aboubekr Belkaid - University of Belkaïd Abou Bekr [Tlemcen], Modelling and Optimisation of the Dynamics of Ecosystems with MICro-organisme (MODEMIC), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), IEEE Control Systems Society. FRA., Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), and Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)

Subjects
Approximation theory, Stochastic process, Stochastic modelling, Context (language use), 02 engineering and technology, Chemostat, 01 natural sciences, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], 010104 statistics & probability, 020401 chemical engineering, Control theory, Nonlinear filter, Filtering problem, 0204 chemical engineering, 0101 mathematics, Biological system, Particle filter, Mathematics
Abstract

International audience; We develop a particle filter approximation of the optimal nonlinear filter in the context of the chemostat. We propose a stochastic model of the chemostat together with an observation model. One of the characteristics of applications in bioprocesses is that the time between two observations is relatively large. We account for this point in the development of the particle filter by refining the prediction step of the particle filter. We present numerical tests on simulated measurements.

Published
2012
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18. An experimental validation of a low-cost indoor relative position localizing system for mobile robotic networks

Author

Giovanni Ulivi, Andrea Gasparri, Attilio Priolo, Maurizio Di Rocco, Alessandro Milano, Institute of Electrical and Electronics Engineers., IEEE Robotics and Automation Society., IEEE Control Systems Society., Mediterranean Control Association., Milano, A, Priolo, A, Gasparri, A, Di Rocco, M, and Ulivi, G

Subjects
Azimuth, Robot kinematics, Engineering, Orientation (computer vision), business.industry, Position (vector), Rendezvous, Robot, Computer vision, Mobile robot, Artificial intelligence, Ceiling (cloud), business
Abstract

In this work, an experimental validation of a low-cost indoor relative position localizing system for mobile robotic networks is described. In our framework, each robot is assumed to be equipped with a light emitter along with a camera, both pointing to the ceiling. In this way, each robot can see on the ceiling a constellation with its own position at the azimuth and the (relative) positions of its neighbors falling in its visual field. This allows to measure the relative distance and orientation among robots. The proposed localizing system can be thought as a convenient tool to validate, among the others, the efficacy of cooperative control algorithms. Several experiments are provided to show the effectiveness of the proposed localizing system for typical multi-robot tasks, such as rendezvous or formation control.

Published
2011
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19. A switching observer for sensorless control of an electromagnetic valve actuator for camless internal combustion engines

Author

Paolo Mercorelli, IEEE Control Systems Society, and European Union Control Association

Subjects
Electric motor, Digital signal processor, Engineering, Observer (quantum physics), observability, business.industry, observer, Estimator, Control engineering, Nonlinear system, Control theory, digital signal processors, Observability, nonlinear systems, Actuator, business, Actuators, Voltage
Abstract

In this paper, the design and operation of a special electromagnetic motor as a variable engine valve actuator are presented. Further, this paper presents feasible approximated velocity switching estimator based on measurements of current and input voltage to achieve sensorless control. This approach avoids a more complex structure for the observer and yields an particular control strategy with an acceptable performance. In general, this approach can represent a viable strategy to build reduced-order observer to estimate not only velocity but also position of a such as type of systems through the measurement of input current and input voltage. This control strategy is presented and discussed as well. Computer simulations of the sensorless control structure are presented in which results are visible in the closed-loop control. © 2011 IEEE. In this paper, the design and operation of a special electromagnetic motor as a variable engine valve actuator are presented. Further, this paper presents feasible approximated velocity switching estimator based on measurements of current and input voltage to achieve sensorless control. This approach avoids a more complex structure for the observer and yields an particular control strategy with an acceptable performance. In general, this approach can represent a viable strategy to build reduced-order observer to estimate not only velocity but also position of a such as type of systems through the measurement of input current and input voltage. This control strategy is presented and discussed as well. Computer simulations of the sensorless control structure are presented in which results are visible in the closed-loop control. © 2011 IEEE.

Published
2011
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20. A multivariable control scheme for a hot dip galvanising line process

Author

Thomas Parisini, Francesco Alessandro Cuzzola, IEEE Control Systems Society, Cuzzola, F. A., and Parisini, Thomas

Subjects
Engineering, business.industry, Multivariable calculus, Process (computing), Control engineering, STRIPS, engineering.material, Automation, Galvanization, law.invention, symbols.namesake, Coating, Control theory, law, symbols, Process control, business, Control Applications
Abstract

Flat strip metal production is realized by means of several consecutive processes where complex control and automation technologies are involved in order to guarantee the best performances and the optimal productivity levels. This paper addresses the galvanizing process and the application of an advanced multivariable controller to the coating process

Published
2010
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21. Distributed Fault Diagnosis of Large-scale Discrete-time Nonlinear Systems: New Results on the Isolation Problem

Author

Ferrari, R. M. G., Parisini, T., Polycarpou, Marios M., IEEE Control Systems Society, Ferrari, R. M. G., Parisini, Thoma, Polycarpou, M. M., and Polycarpou, Marios M. [0000-0001-6495-9171]

Subjects
Interconnection, Engineering, Dynamical systems theory, business.industry, Estimator, Fault (power engineering), Fault detection and isolation, Computer Science::Hardware Architecture, Nonlinear system, Control theory, Isolation (database systems), State (computer science), business, Fault diagnosis
Abstract

This paper deals with the problem of designing a distributed fault detection and isolation methodology for nonlinear discrete-time dynamical systems that are modelled as the interconnection of several subsystems. The subsystems are allowed to overlap, thus sharing some state components. For each subsystem, a Local Fault Diagnoser is designed, based on the measured local state of the subsystem as well as the transmitted variables of neighboring states that define the subsystem interconnections. The local diagnostic decision is made on the basis of the knowledge of the local subsystem dynamic model and of an adaptive approximation of the interconnection with neighboring subsystems. A Global Fault Diagnoser is introduced to isolate distributed faults that cannot be isolated locally. The use of a specially-designed consensus-based estimator is proposed in order to improve the detectability and isolability of faults affecting variables shared among different subsystems. Simulation results are utilized to illustrate of the effectiveness of the proposed distributed fault diagnosis methodology.

Published
2010

22. Decentralized fault detection in a class of large-scale nonlinear uncertain systems

Author

Zhang, X., Polycarpou, Marios M., Parisini, T., IEEE Control Systems Society, X., Zhang, M. M., Polycarpou, Parisini, Thomas, and Polycarpou, Marios M. [0000-0001-6495-9171]

Subjects
Engineering, business.industry, Stability (learning theory), Scale (descriptive set theory), Fault Diagnosis, Fault (power engineering), Upper and lower bounds, Fault detection and isolation, Computer Science::Hardware Architecture, Nonlinear system, Distributed algorithm, Control theory, Symmetric matrix, business
Abstract

This paper presents a decentralized fault detection scheme for a class of distributed large-scale nonlinear uncertain systems. The fault detection architecture consists of interacting local detection filters, one for each subsystem. Under certain assumptions, several important properties of the decentralized fault diagnosis scheme are rigorously investigated. The fault detection threshold for each decentralized detection filter is derived. The detectability analysis characterizes the class of faults that can be detected by the presented scheme. The fault detection time analysis provides an upper bound on the time it takes to detect a fault after its occurrence. The stability and performance analysis deals with the bondededness of all system signals in the adaptive estimation model and characterizes the bounds on the estimation error signals. A simulation example is used to illustrate the effectiveness of the proposed method.

Published
2009
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23. Review of prognostic problem in condition-based maintenance

Author

Eugenia Minca, Rafael Gouriveau, Noureddine Zerhouni, Florin Dragomir, Otilia Elena Dragomir, Dep. of Automation, Computer Science and Elec. Eng, Valahia University of Targoviste [Roumanie] (UVT), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), and IFAC and in collaboration with the IEEE Control Systems Society

Subjects
0209 industrial biotechnology, Engineering, business.industry, Process (engineering), Condition-based maintenance, 02 engineering and technology, Maintenance engineering, Reliability engineering, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, Risk analysis (engineering), General purpose, 0202 electrical engineering, electronic engineering, information engineering, Feature (machine learning), Prognostics, 020201 artificial intelligence & image processing, business
Abstract

International audience; prognostic is nowadays recognized as a key feature in maintenance strategies as it should allow avoiding inopportune maintenance spending. Real prognostic systems are however scarce in industry. That can be explained from different aspects, on of them being the difficulty of choosing an efficient technology ; many approaches to support the prognostic process exist, whose applicability is highly dependent on industrial constraints. Thus, the general purpose of the paper is to explore the way of performing failure prognostics so that manager can act consequently. Diffent aspects of prognostic are discussed. The prognostic process is (re)defined and an overview of prognostic metrics is given. Following that, the "prognostic approaches" are described. The whole aims at giving an overview of the prognostic area, both from the academic and industrial points of views.

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