IFAC-PapersOnLine最新文献_第4页

Numerical Diffusion and its Impact on System-Identification for an Industrial Heating Process

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.016

Ruven Weiss , Moritz Diehl , Johannes Reuter

{"title":"Numerical Diffusion and its Impact on System-Identification for an Industrial Heating Process","authors":"Ruven Weiss , Moritz Diehl , Johannes Reuter","doi":"10.1016/j.ifacol.2025.03.016","DOIUrl":"10.1016/j.ifacol.2025.03.016","url":null,"abstract":"<div><div>This paper deals with system-identification for a distributed parameter heating process where a solid substrate is moving through a spatially extended heating zone and heated up by applying hot air to its surface. The temperature distribution inside the substrate is modeled in a spatial plane, where heat conduction is considered in the direction, perpendicular to the direction of movement. In contrast to previous work, where scalar model parameters (e.g. the thermal parameters of the substrate) have been identified, here, the quantities for the heat transfer (heat transfer coefficient and air temperature) are identified as functions yielding a significantly improved fit to the measurement data. This improved system-identification is performed for two early-lumping modeling approaches, which differ in the way the advection term in the governing Partial Differential Equation is discretized: one uses Eulerian coordinates, where the computational grid is stationary, whereas the second employs Lagrangian coordinates where the grid is moving with the substrate. The differences of the two approaches are discussed with the main focus on numerical diffusion. Especially its impact on the system-identification is investigated: although the fit to the measurement is comparably good in both cases, very different solutions are obtained for the identified functions which, we argue, is due to the optimizer counteracting the smoothing effect of numerical diffusion.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 1","pages":"Pages 85-90"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Soft sensor-based inline geometry control of hole-rolled polygon hubs 基于软传感器的轧孔多边形轮毂在线几何控制

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.023

Viktor Arne , Daniel Spies , Peter Groche

引用次数: 0

Model-based Optimization for Laboratory-Scale Upstream Processing in Monoclonal Antibody Production

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.069

Guilherme A. Pimentel , Camilo Garcia-Tenorio , Radhouane Fekih-Salem , Cédric Toussaint , Ahmed Kanfoud , Thomas Cornet , Thibault Helleputte , Adrien Boes , Riccardo Marega , Alain Vande Wouwer , Laurent Dewasme

引用次数: 0

Robust real-time model parameter extraction in inductive spectroscopy based on Artificial Neural Networks

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.022

Frank Wendler , Ahmed Yahia Kallel , Jeannette Boll , Birgit Awiszus , Till Clausmeyer , Sebastian Härtel , Olfa Kanoun

{"title":"Robust real-time model parameter extraction in inductive spectroscopy based on Artificial Neural Networks","authors":"Frank Wendler , Ahmed Yahia Kallel , Jeannette Boll , Birgit Awiszus , Till Clausmeyer , Sebastian Härtel , Olfa Kanoun","doi":"10.1016/j.ifacol.2025.03.022","DOIUrl":"10.1016/j.ifacol.2025.03.022","url":null,"abstract":"<div><div>Impedance spectrum modelling requires parameter extraction by solving the corresponding inverse identification problem, for which both gradient-based and stochastic methods have been proposed. Stochastic methods are more robust and have a lower risk of getting trapped in local minima but need a long calculation time. In this study, we examine the implementation of artificial neural networks (ANNs) in solving inverse identification problems in inductance spectroscopy, contrasting their performance with robust stochastic methods. In order to overcome the shortage of a representative amount of experimental data, we propose to use the analytically based model to generate accurate enough labelled data for the training process of the ANN. The artificial data have been structured in a homogeneous and tightly spaced grid in the parameter space, thus supporting the model’s generalisation and suppressing overfitting. ANNs with varied degrees of complexity have been investigated by modifying the number of neurons and evaluated by training and comparison with stochastic parameter extraction methods. The investigation concludes that, for the presented application in inductive spectroscopy, the neural networks can provide comparable parameter extraction results with a relative deviation of 0.03 % of the parameter value and a significant reduction in runtime from 60 s to 8 ms.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 1","pages":"Pages 121-126"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On Identifiability and Model Validation of a Population Balance Model for Liquid-Liquid-Mixing⁎

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.033

Terrance Wilms , Daniel Topalovic , Chrysoula Bliatsiou , Jörn Villwock , Matthias Kraume , Andreas Bück , Steffi Knorn

引用次数: 0

State-space modelling approach for control and observer design in property-controlled reverse flow forming

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.020

Lukas Kersting , Bahman Arian , Julian Rozo Vasquez , Ansgar Trächtler , Werner Homberg , Frank Walther

{"title":"State-space modelling approach for control and observer design in property-controlled reverse flow forming","authors":"Lukas Kersting , Bahman Arian , Julian Rozo Vasquez , Ansgar Trächtler , Werner Homberg , Frank Walther","doi":"10.1016/j.ifacol.2025.03.020","DOIUrl":"10.1016/j.ifacol.2025.03.020","url":null,"abstract":"<div><div>Flexible, metal forming processes such as flow forming are exposed to many disturbances that affect geometry and material properties during forming and reduce the reproducibility of those processes. In this context, closed-loop property control is a feasible solution for process improvement. To include advanced controllers and observers in closed-loop property control concepts, mathematical models in terms of state-space models are advantageous. However, especially in case of flow forming these models are not spread due to the complex process kinematics, nonlinearity of the process and spatial dimensions of the workpiece. This makes mathematic state-space modelling challenging. Thus, a model has to be newly developed. This paper therefore presents a novel discrete-time state-space model for flow forming. The model treats the workpiece geometry as discrete and represents the complex process kinematics in the form of a local sampling of the roller trajectory. It can be shown that the model is valid and that the resulting system dynamics especially results the from the displacement between roller and sensor which is considered in the model. Thus, the result of this paper is a valid state-space model that can be prospectively used in a model-based state observer for flow forming. This state observer could later extent a closed-loop property control to enable more complex property structures than before.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 1","pages":"Pages 109-114"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synchronization of Kuramoto oscillators via HEOL, and a discussion on AI

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.040

Emmanuel Delaleau , Cédric Join , Michel Fliess

{"title":"Synchronization of Kuramoto oscillators via HEOL, and a discussion on AI","authors":"Emmanuel Delaleau , Cédric Join , Michel Fliess","doi":"10.1016/j.ifacol.2025.03.040","DOIUrl":"10.1016/j.ifacol.2025.03.040","url":null,"abstract":"<div><div>Artificial neural networks and their applications in deep learning have recently made an incursion into the field of control. Deep learning techniques in control are often related to optimal control, which relies on the Pontryagin maximum principle or the Hamilton-Jacobi-Bellman equation. They imply control schemes that are tedious to implement. We show here that the new HEOL setting, resulting from the fusion of the two established approaches, namely differential flatness and model-free control, provides a solution to control problems that is more sober in terms of computational resources. This communication is devoted to the synchronization of the popular Kuramoto’s coupled oscillators, which was already considered via artificial neural networks by L. Bttcher <em>et al.</em> (Nature Commun., 2022), where, contrarily to this communication, only the single control variable case is examined. One establishes the flatness of Kuramotos coupled oscillator model with multiplicative control and develops the resulting HEOL control. Unlike many examples, this system reveals singularities that are avoided by a clever generation of phase angle trajectories. The results obtained, verified in simulations, show that it is not only possible to synchronize these oscillators in finite time, and even to follow angular frequency profiles, but also to exhibit robustness concerning model mismatches. To the best of our knowledge that has never been done before. Concluding remarks advocate a viewpoint, which might be traced back to Wiener’s cybernetics: control theory belongs to AI.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 1","pages":"Pages 229-234"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-Driven Modelling and Predictive Control for the Geometry and Mechanical Properties of Freeform Bending Processes⁎ 针对自由形态弯曲过程的几何形状和机械性能的数据驱动建模和预测控制⁎

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.021

Ahmed Ismail , Viktor Böhm , Sophie Stebner , Linghao Kong , Wolfram Volk , Sebastian Münstermann , Boris Lohmann

{"title":"Data-Driven Modelling and Predictive Control for the Geometry and Mechanical Properties of Freeform Bending Processes⁎","authors":"Ahmed Ismail , Viktor Böhm , Sophie Stebner , Linghao Kong , Wolfram Volk , Sebastian Münstermann , Boris Lohmann","doi":"10.1016/j.ifacol.2025.03.021","DOIUrl":"10.1016/j.ifacol.2025.03.021","url":null,"abstract":"<div><div>Freeform bending is a technique used to bend different tube profiles into complex structures. In the realm of Aritificial Intelligence and Machine Learning, data-driven approaches in modeling and in optimization based control contribute to the job being executed, by increasing product quality and reducing energy consumption and material waste.</div><div>In previous works, soft-sensors as well as different factors affecting the geometry and the residual stresses have been investigated and been utilized in a preliminary closed-loop control structure. Later on, this control structure has been replaced with a control strategy called <em>Residual Strategy Algorithm</em>, that could, based on previous deviations in the geometry, proactively react in order to reduce their effects. In this paper, the previously developed <em>Residual Strategy Algorithm</em> is extended to include both, the geometry as well as the residual stresses of the tube being bent. Also the modelling of both will be discussed altogether. The validation of the algorithm is done using simulation results.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 1","pages":"Pages 115-120"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modelling View on Numerical Uncertainty Quantification for Dynamical Systems

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.055

Dirk Langemann , Katja Tüting

引用次数: 0

Identification of Vibration Superimposed Motion of a System with Distributed Parameters

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.048

A. Heining , O. Sawodny

引用次数: 0