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187 results on '"Xavier Bombois"'

61. Network topology detection via uncertainty analysis of an identified static model

Author

Håkan Hjalmarsson, Xavier Bombois, Centre National de la Recherche Scientifique (CNRS), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Royal Institute of Technology [Stockholm] (KTH )

Subjects
0209 industrial biotechnology, Dynamic network analysis, Static model, Computer science, Node (networking), 020208 electrical & electronic engineering, Topology (electrical circuits), 02 engineering and technology, Network topology, Topology, Transfer function, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Matrix (mathematics), 020901 industrial engineering & automation, Control and Systems Engineering, 0202 electrical engineering, electronic engineering, information engineering, Uncertainty analysis
Abstract

International audience; In this paper, we propose a methodology to detect the topology of a dynamic network that is based on the analysis of the uncertainty of the static characteristic of the matrix of transfer functions between the external excitations and the node signals.

Published
2021
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73. Least Costly Identification Experiment for the Identification of One Module in a Dynamic Network

Author

Xavier Bombois, Kévin Colin, Laurent Bako, Federico Morelli, Håkan Hjalmarsson, Centre National de la Recherche Scientifique (CNRS), Ampère, Département Automatique pour l'Ingénierie des Systèmes (AIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), ACCESS Linnaeus Center and Department of Automatic Control, and Royal Institute of Technology [Stockholm] (KTH )

Subjects
0209 industrial biotechnology, 020901 industrial engineering & automation, Dynamic network analysis, Control and Systems Engineering, Computer science, 020208 electrical & electronic engineering, 0202 electrical engineering, electronic engineering, information engineering, Control engineering, 02 engineering and technology, Electrical and Electronic Engineering, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

International audience; In this paper we consider the design of least costly experiments for the identification of one module in a given network of locally controlled systems. The identification experiment will be designed in such a way that we obtain a sufficiently accurate model of the to-be-identified module with the smallest identification cost i.e. with the least perturbation of the network.

Published
2021
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75. Data Informativity for the Identification of particular Parallel Hammerstein Systems

Author

Xavier Bombois, Federico Morelli, Kévin Colin, Laurent Bako, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, Computer science, Property (programming), Data Informativity, 020208 electrical & electronic engineering, Vibrating structure gyroscope, Structure (category theory), 02 engineering and technology, Type (model theory), [SPI.AUTO]Engineering Sciences [physics]/Automatic, Identification (information), Consistency (database systems), symbols.namesake, Nonlinear system, 020901 industrial engineering & automation, Additive white Gaussian noise, Control and Systems Engineering, 0202 electrical engineering, electronic engineering, information engineering, symbols, Consistency, Hammerstein Systems, Algorithm, System Identication, Prediction Error Method
Abstract

International audience; To obtain a consistent estimate when performing an identication with Prediction Error, it is important that the excitation yields informative data with respect to the chosen model structure. While the characterization of this property seems to be a mature research area in the linear case, the same cannot be said for nonlinear systems. In this work, we study the data informativity for a particular type of Hammerstein systems for two commonly-used excitations: white Gaussian noise and multisine. The real life example of the MEMS gyroscope is considered.

Published
2020
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77. Data Informativity for the Closed-Loop Identification of MISO ARX Systems

Author

Xavier Bombois, Laurent Bako, Kévin Colin, Centre National de la Recherche Scientifique (CNRS), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
0209 industrial biotechnology, Computer science, Property (programming), Data Informativity, 020208 electrical & electronic engineering, System identification, Structure (category theory), System Identification, 02 engineering and technology, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Consistency (database systems), Identification (information), 020901 industrial engineering & automation, Control and Systems Engineering, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Consistency, Focus (optics), Closed loop, Prediction Error Method
Abstract

International audience; In the Prediction Error identification framework, it is crucial that the collected data are informative with respect to the chosen model structure to get a consistent estimate. In this work, we focus on the data informativity property for the identification of multi-inputs single-output ARX systems in closed-loop and we derive a necessary and sufficient condition to verify if a given multisine external excitation combined with the feedback introduced by the controller yields informative data with respect to the chosen model structure.

Published
2021
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79. Enhanced Power System Damping Estimation via Optimal Probing Signal Design

Author

Vedran S. Peric, Luigi Vanfretti, Abdelkrim Benchaib, S. Boersma, J-C. Gonzalez-Torres, Xavier Bombois, R. Segur, SuperGrid Institute SAS, Centre National de la Recherche Scientifique (CNRS), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Rensselaer Polytechnic Institute (RPI), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Damping Estimation, Optimal Experiment Design, Computer science, 020209 energy, 020208 electrical & electronic engineering, System identification, System Identification, Power Systems, 02 engineering and technology, Variance (accounting), Grid, Signal, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Nonlinear system, Electric power system, Control theory, Power electronics, 0202 electrical engineering, electronic engineering, information engineering, Actuator
Abstract

International audience; For real-time power system dynamic monitoring, it is important to provide accurate estimations of the network's critical electro-mechanical modes, which are time-varying frequency and damping values. This paper employs a framework for designing a multisine probing signal that, when applied in the control inputs of one of the power electronics-based grid actuators, is able to provide a damping estimation with user specified variance. The employed framework is demonstrated through simulations in a nonlinear simulator using models of varying complexity.

Published
2020
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80. Data Informativity for the Open-Loop Identification of MIMO Systems in the Prediction Error Framework

Author

Federico Morelli, Laurent Bako, Xavier Bombois, Kévin Colin, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre for Digital Systems (CERI SN), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), and Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)

Subjects
0209 industrial biotechnology, Property (programming), Computer science, Mean squared prediction error, 020208 electrical & electronic engineering, Data informativity, Open-loop controller, Structure (category theory), System Identification, 02 engineering and technology, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Identification (information), 020901 industrial engineering & automation, Control and Systems Engineering, MIMO Systems, 0202 electrical engineering, electronic engineering, information engineering, Consistency, Electrical and Electronic Engineering, Algorithm, Prediction Error Methods, Mimo systems
Abstract

International audience; In Prediction Error identification, to obtain a consistent estimate of the true system, it is crucial that the input excitation yields informative data with respect to the chosen model structure. We consider in this paper the data informativity property for the identification of a Multiple-Input Multiple-Output system in open loop and we derive conditions to check whether a given input vector will yield informative data with respect to the chosen model structure. We do that for the classical model structures used in prediction-error identification and for the classical types of input vectors, i.e., input vectors whose elements are either multisines or filtered white noises.

Published
2020
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81. The Effect of Prior Knowledge on the Least Costly Identification Experiment

Author

Xavier Bombois, Georgios Birpoutsoukis, Department ELEC [Brussels], Vrije Universiteit Brussel (VUB), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and European Project: 320378,EC:FP7:ERC,ERC-2012-ADG_20120216,SNLSID(2013)

Subjects
0209 industrial biotechnology, Mathematical optimization, Optimization problem, Smoothness (probability theory), Finite impulse response, Computer science, 020208 electrical & electronic engineering, Linear system, System identification, 02 engineering and technology, Transfer function, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Power (physics), [SPI]Engineering Sciences [physics], Identification (information), 020901 industrial engineering & automation, Control and Systems Engineering, Optimal experiment design, Regularization, 0202 electrical engineering, electronic engineering, information engineering, Exponential decay
Abstract

International audience; Design of optimal input excitations is one of the most challenging problems in the field of system identification. The main difficulty lies in the fact that the optimization problem cannot always be formulated to be convex, therefore a globally optimal excitation for the dynamic system of interest cannot be guaranteed. In this paper, optimal input design (OID) for linear systems in the presence of prior knowledge is studied. Information related to exponential decay and smoothness is incorporated in the optimal input design problem by making use of the Bayes rule of information. Three different cases of modeling the linear dynamics are considered, namely Finite Impulse Response (FIR) model with and without prior knowledge, as well as the rational transfer function case. It is shown that the prior information affects the spectrum of the minimum power optimal input. The input with the least power is always obtained for the transfer function model case.

Published
2018
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82. Application-Oriented Input Design in System Identification: Optimal Input Design for Control [Applications of Control]

Author

Mariette Annergren, Håkan Hjalmarsson, Christian A. Larsson, Xavier Bombois, Bo Wahlberg, Department of Automatic Control, Royal Institute of Technology [Stockholm] (KTH ), KTH School of Electrical Engineering, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Centre of Autonomous Systems (KTH)

Subjects
0209 industrial biotechnology, Engineering, business.industry, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Control (management), System identification, Control engineering, 02 engineering and technology, model-based control design, 020901 industrial engineering & automation, Input design, Control and Systems Engineering, Real-time Control System, Robustness (computer science), Modeling and Simulation, optimal input design, 0202 electrical engineering, electronic engineering, information engineering, Key (cryptography), 020201 artificial intelligence & image processing, application-oriented input design, Electrical and Electronic Engineering, Robust control, business, system identification
Abstract

International audience; Model-based control design plays a key role in today's industrial practice, and industry demands cuttingedge methods for identifying the necessary models. However, additional tools are needed to handle the increasingly stringent conditions on cost and performance related to identifying the models.

Published
2017
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83. Non-intrusive identification of hydro power plants' dynamics using control system measurements

Author

Xavier Bombois, Kjetil Uhlen, Sigurd Hofsmo Jakobsen, Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Centre National de la Recherche Scientifique (CNRS), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Power station, Computer science, 020209 energy, 020208 electrical & electronic engineering, Monte Carlo method, Energy Engineering and Power Technology, Control engineering, 02 engineering and technology, Transfer function, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Identification (information), Electric power system, Hydroelectricity, Hydro power, Control system, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering
Abstract

In this paper we propose two non-intrusive methods for identifying hydro power plant dynamics using standard system identification techniques. The purpose of the tests is to obtain transfer functions relevant for the frequency containment reserves delivered by hydro power plants. To validate the methods, we analytically demonstrate under which conditions the methods will yield consistent results. Moreover, using a simulation example we discuss the validity of the methods when one of the conditions is not met. Results using measurements from the control system of a power plant in the Nordic power system are also provided.Our proposed methods also allow us to identify a transfer function that can be used to check new requirements developed by the Nordic TSOs. The transfer functions obtained by our methods is compared with the transfer function obtained using the TSOs’ methods using Monte Carlo Simulation. https://doi.org/10.1016/j.ijepes.2020.106180 © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/)

Published
2020
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84. Data Informativity for the Identification of MISO FIR Systems with Filtered White Noise Excitation

Author

Laurent Bako, Xavier Bombois, Federico Morelli, Kévin Colin, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre for Digital Systems (CERI SN), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), and Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)

Subjects
0209 industrial biotechnology, Finite impulse response, 020208 electrical & electronic engineering, Structure (category theory), Spectral density, White noise excitation, 02 engineering and technology, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Identification (information), Matrix (mathematics), 020901 industrial engineering & automation, Positive definiteness, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, 0202 electrical engineering, electronic engineering, information engineering, Identifiability, Algorithm, Mathematics
Abstract

International audience; For Prediction Error Identication, there are two main ingredients to get a consistent estimate: one of them is the data informativity with respect to (w.r.t.) the considered model structure. One common criterion used for the informativity is the positive deniteness of the input density spectral power (DSP) matrix at all frequencies. This criterion is not appropriate for multisine excitation but can be used for ltered white noise excitation for many identication problems. However, this criterion is not necessary and its application for some identication problems might not be possible. In this paper, we propose a necessary and sucient condition for the data informativity in the case of multiple-inputs single-output (MISO) nite impulse response (FIR) model structure in open-loop.

Published
2019
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85. LPV system identification for control using the local approach

Author

Xavier Bombois, Julien Huillery, Gérard Scorletti, Debarghya Ghosh, Centre National de la Recherche Scientifique (CNRS), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
0209 industrial biotechnology, identification for control, Computer science, Design of experiments, System identification, 02 engineering and technology, Computer Science Applications, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, LPV system identification, Control and Systems Engineering, Control theory, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Optimal identification experiment design
Abstract

International audience; In this paper, we consider the problem of optimal experiment design for LPV system identification with the local approach when the identified model has to be used for LPV control. This local approach for LPV system identification is characterised by a number of local LTI identification experiments performed at constant values of the scheduling variable. In this paper, we determine these constant values of the scheduling variable as well as the input spectra of the corresponding local LTI identification experiments in an optimal way. The optimal LPV identification experiment is here defined as the experiment with the least input energy while guaranteeing that the identified LPV model is sufficiently accurate to yield a satisfactory LPV controller.

Published
2019
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86. Identification-Based Approach for Electrical Coupling Compensation in a MEMS Gyroscope

Author

Anton Korniienko, Fabricio Saggin, Xavier Bombois, Gérard Scorletti, Kévin Colin, Christophe Le Blanc, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Centre National de la Recherche Scientifique (CNRS)

Subjects
parasitic coupling, model structure, 0209 industrial biotechnology, Computer science, electrostatic actuators, 02 engineering and technology, 01 natural sciences, detection circuits, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Compensation (engineering), law.invention, 020901 industrial engineering & automation, Control theory, law, parasitic effects, parasitic electrical coupling, Electronic circuit, electrical coupling model, Coupling, multivariable framework, Multivariable calculus, 010401 analytical chemistry, Vibrating structure gyroscope, mechanical modes, parasitic cross-couplings, MEMS gyroscope, Gyroscope, nonlinear behavior, electrical coupling compensation, 0104 chemical sciences, Nonlinear system, actuation, identification-based approach, Actuator, multivariable identification
Abstract

International audience; This work consists of a new approach to identify and compensate the parasitic electrical coupling between the excitation and the detection circuits of a MEMS gyroscope. Based on multivariable identification and the nonlinear behavior of electrostatic actuators, we propose a systematic and flexible way to model the mechanical modes as well as the parasitic coupling. The electrical coupling model is then used to compensate the parasitic effects of the device. Our main contributions are: (i) no model structure is enforced, so all the dynamics between actuation and detection are considered; and (ii) the multivariable framework allows also identifying the parasitic cross-couplings.

Published
2019
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87. Active vibration control in specific zones of smart structures

Author

Ellen Skow, Peng Wang, Manuel Collet, Kévin Colin, Xavier Bombois, Anton Korniienko, Gérard Scorletti, Chuhan Wang, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de Tribologie et Dynamique des Systèmes (LTDS), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Ecole Nationale d'Ingénieurs de Saint Etienne-Centre National de la Recherche Scientifique (CNRS), and Université de Lyon

Subjects
Beam-piezo system, Grey-box identification, 0209 industrial biotechnology, Computer science, Frequency band, 02 engineering and technology, Smart material, H ∞ control, Vibration energy, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, Robustness (computer science), Control theory, Active vibration control, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Control objective, Model reduction, Applied Mathematics, 020208 electrical & electronic engineering, Robust stability, Computer Science Applications, Vibration, Control and Systems Engineering, [SPI.MECA.STRU]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Structural mechanics [physics.class-ph], MIMO feedback controller
Abstract

Smart structures are light structures with integrated sensing and actuating capabilities (smart materials). In this paper, the use of such smart materials for active vibration control is considered, in the case where the vibration covers a large frequency band and the vibration has to be reduced in a region where neither actuation nor sensing is possible. An accurate model combining physical and data-based modeling is developed. A multi-variable H ∞ controller achieving the desired control objective and taking into account the robustness issues is computed. The validity of the proposed approach is verified on an experimental setup.

Published
2019
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88. Probing signal design for enhanced damping estimation in power networks

Author

Xavier Bombois, Luigi Vanfretti, Sjoerd Boersma, Abdelkrim Benchaib, Juan Carlos Gonzalez-Torres, SuperGrid Institute SAS, Centre National de la Recherche Scientifique (CNRS), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Rensselaer Polytechnic Institute (RPI)

Subjects
Power networks, Optimization problem, Computer science, 020209 energy, 020208 electrical & electronic engineering, Linear matrix inequality, System identification, Energy Engineering and Power Technology, Spectral density, 02 engineering and technology, Signal, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Power (physics), Nonlinear system, Damping estimation, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Realization (systems), Experiment design
Abstract

International audience; Electromechanical oscillations are inherent to power networks. Although it is possible to partially damp these oscillations, it is impossible to eliminate them completely. This oscillatory behavior can lead to major breakdowns in power networks, especially when the damping is relatively low. It is therefore important to provide accurate estimations of the network’s damping values. These estimation can be obtained via system identification for which a probing signal needs to be designed. This paper presents a framework for designing a specific probing signal that is able to provide accurate damping estimations with a user-defined variance. A power spectrum of the probing signal is determined by solving an optimization problem with Linear Matrix Inequality constraints. The objective function is defined as a weighted sum of the probing signal’s power and a level of disturbance caused by probing the network. A desired level of the damping estimation’s variance is set as a constraint. The time-domain realization of the obtained power spectrum is described by a multisine, which is the actual probing signal applied to the network. The employed framework is demonstrated through nonlinear simulations using the Kundur with an embedded HVDC link and NORDIC 44 networks.

Published
2021
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89. Hierarchical Robust Analysis for Identified Systems in Network

Author

Xavier Bombois, Gérard Scorletti, Anton Korniienko, Håkan Hjalmarsson, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Royal Institute of Technology [Stockholm] (KTH ), Laboratoire Ampère, KTH Royal institute of technology, Ecole Centrale Lyon, Université de Lyon, ACCESS Linnaeus Center and Department of Automatic Control, and Région Rhône-Alpes Auvergne

Subjects
0209 industrial biotechnology, Computational complexity theory, Computer science, Computation, 020208 electrical & electronic engineering, Network, 02 engineering and technology, Systems and Control (eess.SY), computer.software_genre, Ellipsoid, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, Control and Systems Engineering, Robustness (computer science), Computer Science::Systems and Control, Multi-Agents, Interconnected systems, 0202 electrical engineering, electronic engineering, information engineering, Identification for Control, FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Systems and Control, Data mining, Robust analysis, computer
Abstract

International audience; This paper considers worst-case robustness analysis of a network of locally controlled uncertain systems with uncertain parameter vectors belonging to the ellipsoid sets found by identification procedures. In order to deal with computational complexity of large-scale systems, an hierarchical robustness analysis approach is adapted to these uncertain parameter vectors thus addressing the trade-off between the computation time and the conservatism of the result.

Published
2018
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90. Identification of hydro turbine governors using PMU data

Author

Xavier Bombois, Sigurd Hofsmo Jakobsen, Kjetil Uhlen, Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and The work presented in this paper was carried out in the project OperaGrid funded by the Norwegian research council. In addition the ELECTRA IRP FP7 project funded the research exchange between NTNU and Ampere Lab.

Subjects
Closed-loop transfer function, Hydraulic turbines, Computer science, 020209 energy, Phasor measurement units, 02 engineering and technology, Transfer function, Turbine, Automotive engineering, Power (physics), Generators, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Power flow, Electric power system, Identification (information), [SPI]Engineering Sciences [physics], Transfer functions, Power system dynamics, 0202 electrical engineering, electronic engineering, information engineering, Governor
Abstract

Recent concerns for the frequency quality in the Nordic power system has lead to an increased interest in hydro turbine governors. Among this research have been papers on identification of turbine and turbine governor dynamics from PMU measurements. However, no attempt at a theoretical validation has been made. This paper fills in this gap by a theoretical validation using a DC power flow model for modelling the power flows in the grids. By doing this it is shown that it is indeed possible to identify the closed loop transfer function of the turbine, turbine governor and electromechanical dynamics. An experimental validation using results from a real life power system is also presented. © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Published
2018
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91. Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

Author

Mehdi Mansoori, Xavier Bombois, M.G. Potters, Paul M.J. Van den Hof, Delft Center for Systems and Control [Delft] (DCSC), Delft University of Technology (TU Delft), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Chemical and Petroleum Engineering, Sharif University of Technology, Department of Electrical Engineering, Technische Universiteit Eindhoven, Technische Universiteit Eindhoven (TU/e), Control Systems, and Dynamic Networks: Data-Driven Modeling and Control

Subjects
0209 industrial biotechnology, Mathematical optimization, Engineering, Dynamical systems theory, 0208 environmental biotechnology, Physical system, 02 engineering and technology, Distributed systems, Stability (probability), [SPI.AUTO]Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, Distributed parameter system, accurate, Scaling, optimal experiment design, Estimation theory, business.industry, Design of experiments, simulation, 020801 environmental engineering, Computer Science Applications, Control and Systems Engineering, physical systems, identification, Actuator, business, optimal actuator and sensor locations
Abstract

International audience; Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.

Published
2016
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92. Experimental evaluation of model predictive control with excitation (MPC-X) on an industrial depropanizer

Author

Håkan Hjalmarsson, Christian A. Larsson, Xavier Bombois, and Cristian R. Rojas

Subjects
Design modification, Engineering, business.industry, Wear and tear, Design of experiments, Linear matrix inequality, Control engineering, Industrial and Manufacturing Engineering, Computer Science Applications, Model predictive control, Control and Systems Engineering, Fractionating column, Control theory, Modeling and Simulation, business, Excitation
Abstract

It is commonly observed that over the lifetime of most model predictive controllers, the achieved performance degrades over time. This effect can often be attributed to the fact that the dynamics of the controlled plant change as the plant ages, due to wear and tear, refurbishment and design changes of the plant, to name a few factors. These changes mean that re-identification is necessary to restore the desired performance of the controller. An extension of existing predictive controllers, capable of producing signals suitable for closed loop re-identification, is presented in this article. The main contribution is an extensive experimental evaluation of the proposed controller for closed loop re-identification on an industrial depropanizer distillation column in simulations and in real experiments. The plant experiments are conducted on the depropanizer during normal plant operations. In the simulations, as well as in the experiments, the updated models from closed loop re-identification result in improvement of the performance. The algorithm used combines regular model predictive control with ideas from applications oriented input design and linear matrix inequality based convex relaxation techniques. Even though the experiments show promising result, some implementation problems arise and are discussed.

Published
2015
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93. Optimal identification experiment design for LPV systems using the local approach

Author

Guillaume Mercère, Debarghya Ghosh, Xavier Bombois, Julien Huillery, Gérard Scorletti, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire d'Informatique et d'Automatique pour les Systèmes (LIAS), and Université de Poitiers-ENSMA

Subjects
0209 industrial biotechnology, Mathematical optimization, Engineering, business.industry, Design of experiments, 020208 electrical & electronic engineering, [SPI.NRJ]Engineering Sciences [physics]/Electric power, System identification, 02 engineering and technology, Scheduling (computing), 020901 industrial engineering & automation, LPV system identification, Control and Systems Engineering, Control theory, Computer Science::Systems and Control, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, business, Optimal identification experiment design
Abstract

International audience; In this paper, we consider the problem of optimally designing the experimental conditions for LPV system identification with the local approach. Such an LPV system identification experiment is characterized by a number of local LTI identification experiments performed at constant values of the scheduling variable. The main contribution of this paper is to determine these constant values of the scheduling variable as well as the input spectra of the corresponding local LTI identification experiments in order to obtain a user-defined model accuracy with the least input energy.

Published
2018
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94. Batch-to-batch model improvement for cooling crystallization

Author

Xavier Bombois, Ali Mesbah, Marco Forgione, Georgios Birpoutsoukis, Peter J. Daudey, Paul M.J. Van den Hof, Control Systems, Dynamic Networks: Data-Driven Modeling and Control, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Vrije Universiteit Brussel (VUB), Department of Mathematics [Berkeley], University of California [Berkeley], University of California-University of California, Delft University of Technology (TU Delft), Eindhoven University of Technology [Eindhoven] (TU/e), Electricity, and Faculty of Engineering

Subjects
Computer Science::Machine Learning, 0209 industrial biotechnology, Engineering, Iterative learning control, Model prediction, iterative learning control, Model parameters, 02 engineering and technology, law.invention, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Process Control, 020901 industrial engineering & automation, 020401 chemical engineering, Control theory, law, Process control, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, 0204 chemical engineering, Crystallization, Electrical and Electronic Engineering, System identification, Batch processes, Batch cooling crystallization, business.industry, Applied Mathematics, Mechanical Engineering, System Identification, Computer Science Applications, Term (time), Industrial Engineering & Automation, Control and Systems Engineering, Scientific method, business
Abstract

Two batch-to-batch model update strategies for model-based control of batch cooling crystallization are presented. In Iterative Learning Control, a nominal process model is adjusted by a non-parametric, additive correction term which depends on the difference between the measured output and the model prediction in the previous batch. In Iterative Identification Control, the uncertain model parameters are iteratively estimated using the measured batch data. Due to the different nature of the model update, the two algorithms have complementary advantages and disadvantages which are investigated in a simulation study and through experiments performed on a pilot-scale crystallizer. (C) 2015 Elsevier Ltd. All rights reserved.

Published
2015
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95. Trajectory planning and trajectory tracking for a small-scale helicopter in autorotation

Author

Paul M.J. Van den Hof, Skander Taamallah, Xavier Bombois, Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Control Systems, Dynamic Networks: Data-Driven Modeling and Control, and Cyber-Physical Systems Center Eindhoven

Subjects
0209 industrial biotechnology, Engineering, Scale (ratio), Robust control, 02 engineering and technology, Tracking (particle physics), 020901 industrial engineering & automation, 0203 mechanical engineering, Autorotation, Control theory, Electrical and Electronic Engineering, 020301 aerospace & aeronautics, business.industry, Applied Mathematics, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Differential flatness, Unmanned aerial vehicle, Computer Science Applications, Nonlinear system, Small-scale helicopter autorotation, Control and Systems Engineering, Trajectory planning, Control system, Trajectory, business
Abstract

International audience; The design of a high-performance guidance and control system for a small-scale helicopterUnmanned Aerial Vehicle (UAV), with an engine OFF flight condition (i.e. autorotation), is known to be a challenging task. It is the purpose of this paper to present a Trajectory Planning (TP) and Trajectory Tracking (TT) system, having onlinecomputational tractability. The presented Flight Control System (FCS) is anchored within the aggregated paradigms of differential flatness based optimal planning, and robust control based tracking. In particular the first real-time feasible, model-based TP and model-based TT, for a small-scale helicopter in autorotation is being demonstrated using a high-fidelity, high-order, nonlinear helicopter simulation.

Published
2017
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96. Optimal Signal Selection for Power System Ambient Mode Estimation Using a Prediction Error Criterion

Author

Vedran S. Peric, Xavier Bombois, Luigi Vanfretti, Royal Institute of Technology [Stockholm] (KTH ), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Damping ratio, Engineering, prediction error, Optimality criterion, business.industry, 020209 energy, Mode (statistics), Energy Engineering and Power Technology, Estimator, signal selection, 02 engineering and technology, Signal, PMU placement, Mode estimation, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Delta method, Electric power system, Control theory, 0202 electrical engineering, electronic engineering, information engineering, mode meter, Autoregressive–moving-average model, Electrical and Electronic Engineering, business
Abstract

International audience; This paper formulates an optimality criterion for the selection of synchrophasor signals to be used in ambient mode estimators. This criterion, which is associated with each measured signal and each dominant mode, is defined as the asymptotic variance of the corresponding estimated mode damping ratio. The value of the criterion is computed directly from an estimated autoregressive moving average (ARMA) model. Because the online computation of the defined criterion (for each measured signal in the system) may be computationally expensive, a fast pre-selection method for initial signal ranking is formulated. The pre-selection method is used to effectively determine a set of the candidate signals for which the formal criterion is evaluated in a second stage. The methodology is illustrated using synthetic measurements from the KTH Nordic 32 and the IEEE 39-bus test systems.

Published
2016
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97. An application-oriented approach to dual control with excitation for closed-loop identification

Author

Cristian R. Rojas, Afrooz Ebadat, Christian A. Larsson, Håkan Hjalmarsson, Xavier Bombois, ACCESS Linnaeus Center and Department of Automatic Control, Royal Institute of Technology [Stockholm] (KTH ), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and European Project: 257059,EC:FP7:ICT,FP7-ICT-2009-5,AUTOPROFIT(2010)

Subjects
0209 industrial biotechnology, Engineering, Closed-loop identification, Optimization problem, business.industry, General Engineering, System identification, 02 engineering and technology, Optimal control, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Identification (information), Model predictive control, Constrained systems, 020901 industrial engineering & automation, 020401 chemical engineering, Control theory, Time domain, Markov decision process, 0204 chemical engineering, business, Input design
Abstract

International audience; Identification of systems operating in closed loop is an important problem in industrial applications, where model-based control is used to an increasing extent. For model-based controllers, plant changes over time eventually result in a mismatch between the dynamics of any initial model in the controller and the actual plant dynamics. When the mismatch becomes too large, control performance suffers and it becomes necessary to re-identify the plant to restore performance. Often the available data are not informative enough when the identification is performed in closed loop and extra excitation needs to be injected. This paper considers the problem of generating such excitation with the least possible disruption to the normal operations of the plant. The methods explicitly take time domain constraints into account. The formulation leads to optimal control problems which are in general very difficult optimization problems. Computationally tractable solutions based on Markov decision processes and model predictive control are presented. The performance of the suggested algorithms is illustrated in two simulation examples comparing the novel methods and algorithms available in the literature.

Published
2016
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98. A Waveform Design Method for a Piezo Inkjet Printhead Based on Robust Feedforward Control

Author

Sjirk Koekebakker, Robert Babuska, W. de Zeeuw, Amol A. Khalate, Xavier Bombois, Gérard Scorletti, Delft Center for Systems and Control [Delft] (DCSC), Delft University of Technology (TU Delft), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
0209 industrial biotechnology, Engineering, 02 engineering and technology, Residual, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Physics::Fluid Dynamics, Tracking error, Physics::Popular Physics, 020901 industrial engineering & automation, Control theory, Waveform, Electrical and Electronic Engineering, ComputingMilieux_MISCELLANEOUS, Parametric statistics, business.industry, Mechanical Engineering, Feed forward, Robust optimization, 021001 nanoscience & nanotechnology, Computer Science::Other, Inkjet printhead, microelectromechanical systems (MEMS), robust feedforward control, Robust control, 0210 nano-technology, Actuator, business, optimization
Abstract

The printing quality delivered by a Drop-on-Demand (DoD) piezo inkjet printhead is limited mainly due to the residual oscillations in the ink channel. The maximal jetting frequency of a DoD inkjet printhead can be increased by quickly damping the residual oscillations and thus bringing an ink channel to rest after jetting an ink drop. In this paper, we propose a robust optimization-based method to design the input actuation waveform for the piezo actuator in order to improve the damping of the residual oscillations in the presence of parametric uncertainties in the ink-channel model. The proposed method obtains a robust actuation pulse by minimizing the tracking error under the parametric uncertainty. Experimental results with a small-droplet DoD inkjet printhead are presented to show the efficacy of the proposed method and the significant improvement in the ink drop consistency.

Published
2012
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100. Performance improvement of a drop-on-demand inkjet printhead using an optimization-based feedforward control method

Author

R. Waarsing, Herman Wijshoff, Xavier Bombois, Amol A. Khalate, Robert Babuska, and Delft University of Technology (TU Delft)

Subjects
Engineering, 02 engineering and technology, Residual, 01 natural sciences, Transfer function, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Physics::Fluid Dynamics, Control theory, 0103 physical sciences, Electronic engineering, Waveform, Electrical and Electronic Engineering, ComputingMilieux_MISCELLANEOUS, ComputingMethodologies_COMPUTERGRAPHICS, 010302 applied physics, Inkwell, business.industry, Applied Mathematics, Drop (liquid), Feed forward, 021001 nanoscience & nanotechnology, Computer Science Applications, Computer Science::Other, Control and Systems Engineering, Performance improvement, 0210 nano-technology, Actuator, business
Abstract

The printing quality delivered by a drop-on-demand (DoD) inkjet printhead is limited due to the residual oscillations in the ink channel. The maximal jetting frequency of a DoD inkjet printhead can be increased by quickly damping the residual oscillations and by bringing in this way the ink channel to rest after jetting the ink drop. This paper proposes an optimization-based method to design the input actuation waveform for the piezo actuator in order to improve the damping of the residual oscillations. A discrete-time transfer function derived from the narrow-gap model is used to predict the response of the ink channel under the application of the piezo input. Simulation and experimental results are presented to show the applicability of the proposed method.

Published
2011
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