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Control of operability of Peltier modules in cooling systems based on the analysis of transient operating modes

ARCHIVES OF THERMODYNAMICS 2021年第2期42卷 31-42页

作者： Kuzichkin, Oleg Rudolfovich Konstantinov, Igor Sergeevich Vasilyev, Gleb Sergeevich Surzhik, Dmitry Igorevich Belgorod State Univ Pobedy 85 Belgorod 308015 Russia Russian State Agr Univ Moscow Timiryazev Agr Acad Listvennichnaya 5 Moscow 127550 Russia

The paper is devoted to the control of operability of Peltier modules based on the analysis of transient modes of their operation. Advantages of using low-power thermoelectric modules for the development of thermoelectric plants with adaptive control systems for the needs of the agricultural complex, which significantly reduce their cost characteristics, are shown. The problem of using the stationary mode of their operation, associated with the low efficiency of the modules, as well as the dynamic mode, associated with the presence of transient processes, is indicated. It is noted that overcoming this problem requires solution of the task of automation of reliability providing the well-known approaches to its solution are shown, for which the key advantages and disadvantages are given. An approach is proposed to complex control of the operability and quality of thermoelectric modules during their expluatation in three components of the physical process of thermoelectric conversion (Peltier thermoelectric effect, electrical and thermal transfer phenomena) by analyzing transients in the system based on identification algorithms. To justify it, the necessary equations and mathematical relations are given. Aprobating of the proposed approach was carried out experimentally by determining the time constants for operable and defective commercially available modules and showed its significant advantages over the standard verification procedure.

关键词： Thermoelectric systems Agriculture complex Transients Peltier effect identification algorithms

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Estimating models with high-order noise dynamics using semi-parametric weighted null-space fitting

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AUTOMATICA 2019年 102卷 45-57页

作者： Galrinho, Miguel Rojas, Cristian R. Hjalmarsson, Hakan KTH Royal Inst Technol Sch Elect Engn & Data Sci Dept Automat Control SE-10044 Stockholm Sweden

Standard system identification methods often provide inconsistent estimates with closed-loop data. With the prediction error method (PEM), this issue is solved by using a noise model that is flexible enough to capture the noise spectrum. However, a too flexible noise model (i.e., too many parameters) increases the model complexity, which can cause additional numerical problems for PEM. In this paper, we consider the weighted null-space fitting (WNSF) method. With this method, the system is first modeled using a non-parametric ARX model, which is then reduced to a parametric model of interest using weighted least squares. In the reduction step, a parametric noise model does not need to be estimated if it is not of interest. Because the flexibility of the noise model is increased with the sample size, this will still provide consistent estimates in closed loop and asymptotically efficient estimates in open loop. In this paper, we prove these results, and we derive the asymptotic covariance for the estimation error obtained in closed loop, which is optimal for an infinite-order noise model. For this purpose, we also derive a new technical result for geometric variance analysis, instrumental to our end. Finally, we perform a simulation study to illustrate the benefits of the method when the noise model cannot be parametrized by a low-order model. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： System identification Closed-loop identification Non-parametric identification Parameter identification identification algorithms Least squares

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Benchmark problems for continuous-time model identification: Design aspects, results and perspectives

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AUTOMATICA 2019年 107卷 511-517页

作者： Pascu, Valentin Garnier, Hugues Ljung, Lennart Janot, Alexandre ONERA French Aerosp Lab Syst Control & Flight Dynam Dept F-31055 Toulouse France Univ Lorraine CRAN UMR 7039 F-54519 Vandoeuvre Les Nancy France CNRS CRAN UMR 7039 F-54506 Vandoeuvre Les Nancy France Linkoping Univ Div Automat Control SE-58183 Linkoping Sweden

The problem of estimating continuous-time model parameters of linear dynamical systems using sampled time-domain input and output data has received considerable attention over the past decades and has been approached by various methods. The research topic also bears practical importance due to both its close relation to first principles modelling and equally to linear model-based control design techniques, most of them carried in continuous time. Nonetheless, as the performance of the existing algorithms for continuous-time model identification has seldom been assessed and, as thus far, it has not been considered in a comprehensive study, this practical potential of existing methods remains highly questionable. The goal of this brief paper is to bring forward a first study on this issue and to factually highlight the main aspects of interest. As such, an analysis is performed on a benchmark designed to be consistent both from a system identification viewpoint and from a control-theoretic one. It is concluded that robust initialization aspects require further research focus towards reliable algorithm development. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： identification algorithms Output error identification Parameter identification Linear multivariable systems Benchmark examples Monte Carlo simulation

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A method of online traction parameter identification and mapping

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IFAC-PapersOnLine 2020年第2期53卷 13933-13938页

作者： Alexander Kobelski Pavel Osinenko Stefan Streif Technische Universität Chemnitz Automatic Control and System Dynamics Laboratory Germany

Fuel consumption of heavy-duty vehicles such as tractors, bulldozers etc. is comparably high due to their scope of operation. The operation settings are usually fixed and not tuned to the environmental factors, such as ground conditions. Yet exactly the ground-to-propelling-unit properties are decisive in energy efficiency. Optimizing the latter would require a means of identifying those properties. This is the central matter of the current study. More specifically, the goal is to estimate the ground conditions from the available measurements, such as drive train signals, and to establish a map of those. The ground condition parameters are estimated using an adaptive unscented Kalman filter. A case study is provided with the actual and estimated ground condition maps. Such a mapping can be seen as a crucial milestone in optimal operation control of heavy-duty vehicles.

关键词： Traction control identification algorithms Data storage Kalman filters Dynamic modelling Vehicle Dynamics

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TRIP-ID: A tool for a smart and interactive identification of Magic Formula tyre model parameters from experimental data acquired on track or test rig

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2018年 102卷 1-22页

作者： Farroni, Flavio Lamberti, Raffaele Mancinelli, Nicolo Timpone, Francesco Univ Naples Federico II Dipartimento Ingn Ind Via Claudio 21 I-80125 Naples Italy Ducati Motor Holding Spa Ducati Corse Div Vehicle Dynam Via Cavalieri Ducati 3 I-40132 Bologna Italy

Tyres play a key role in ground vehicles' dynamics because they are responsible for traction, braking and cornering. A proper tyre-road interaction model is essential for a useful and reliable vehicle dynamics model. In the last two decades Pacejka's Magic Formula (MF) has become a standard in simulation field. This paper presents a Tool, called TRIP-ID (Tyre Road Interaction Parameters identification), developed to characterize and to identify with a high grade of accuracy and reliability MF micro-parameters from experimental data deriving from telemetry or from test rig. The tool guides interactively the user through the identification process on the basis of strong diagnostic considerations about the experimental data made evident by the tool itself. A motorsport application of the tool is shown as a case study. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Tyre Road Interaction Magic Formula (MF) Tyre model parameters identification algorithms Smart identification Interactive identification Vehicle dynamics

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Laguerre based predictors in discrete-time recursive algorithms: A solution for open-loop identification under oversampling

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IFAC-PapersOnLine 2017年第1期50卷 12911-12918页

作者： Vau, Bernard Bourlès, Henri SATIE Ecole normale supérieure de Cachan Cachan94230 France

In this paper we propose a novel formulation of the predictor used in open-loop recursive identification algorithms. The predicted output is expressed by means of an orthogonal Laguerre transfer functions basis. This predictor representation presents many advantages: It makes it possible to identify robustly oversampled systems without any bias in low frequency, and to obtain relevant reduced order models. The Laguerre pole plays the role of a tuning parameter enabling the selection of the best approximation frequency area. The proposed schemes address both output error and ARMAX systems. Simulation and experimental results show all the practical benefits provided by these algorithms. © 2017

关键词： Transfer functions Orthogonal functions Adaptive Control ARMAX model identification algorithms Laguerre Output error models Recursive algorithms Recursive estimation

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Time domain diffusion parameters identification of electrochemical impedance models using fractional order system

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IFAC-PapersOnLine 2018年第15期51卷 377-382页

作者： Eddine, Achraf Nasser Huard, Benoît Gabano, Jean-Denis Poinot, Thierry Thomas, Anthony Martemianov, Serguei Université de Poitiers LIAS 2 rue Pierre Brousse TSA 41105 cedex 9 Poitiers86073 France Université de Poitiers Institut Pprime 2 rue Pierre Brousse TSA 41105 cedex 9 Poitiers86073 France

In this paper, identification of the diffusion impedance parameters of an electrochemical cell in time domain is presented. As Electrochemical Impedance Spectroscopy (EIS) requires long time to obtain experimental data for low frequencies, a method using chronopotentiometric experiments is studied in order to reach more quickly diffusion parameters. The electrochemical cell is modeled using an equivalent electrical circuit describing separately the charge transfer and the diffusion phenomena. The electrochemical model provides then a transfer function whose parameters can be identified only in the frequency domain. Thus, thanks to a fractional operator approximation, a half order integrator is able to perform simulations in the time domain. Therefore, a fractional model is proposed in order to identify the slow dynamics due to diffusion thanks to the Levenberg-Marquardt algorithm. Experimental results obtained from an electrochemical test-bench including Ferri-Ferro solution demonstrate the interest of fractional modeling. Diffusion parameters are identified in the time domain and cross-validation in the frequency domain using EIS measurements demonstrates the relevance of the proposed method. © 2018

关键词： Time domain analysis Charge transfer Diffusion Electrochemical cells Electrochemical impedance spectroscopy Frequency domain analysis Parameter estimation Solar cells Spectroscopy State space methods Chronopotentiometry Electrochemical impedance Electrochemical modeling Equivalent electrical circuits Fractional model identification algorithms Levenberg Marquardt algorithm State space models

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identification of influential spreaders based on classified neighbors in real-world complex networks

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APPLIED MATHEMATICS AND COMPUTATION 2018年 320卷 512-523页

作者： Li, Chao Wang, Li Sun, Shiwen Xia, Chengyi Tianjin Univ Technol Tianjin Key Lab Intelligence Comp & Novel Softwar Tianjin 300384 Peoples R China Tianjin Univ Technol Minist Educ Key Lab Comp Vis & Syst Tianjin 300384 Peoples R China

Identifying the influential spreaders in complex network is a very important topic, which is conducive to deeply understanding the role of nodes in the information diffusion and epidemic spreading among a population. To this end, in this paper, we propose a novel classified neighbors algorithm to quantify the nodal spreading capability and further to differentiate the influence of various nodes. Here, we believe that the contribution of different neighbors to their focal node is different, and then classify the neighbors of the focal node according to the removal order of the neighbor in the process of k-shell decomposition. By assigning different weights for each class of neighbors and summing up the neighbors' contributions, the spreading capacity of the focal node can be accurately characterized. Through extensive simulation experiments over 9 real-world networks, the weight distribution of different types of neighbors has been optimized, and the results strongly indicate that the current algorithm has the higher ranking accuracy and differentiation extent when compared to other algorithms, such as degree centrality, k-shell decomposition method and mixed degree decomposition approach. Current results can help to greatly reduce the cost of sales promotion, considerably suppress the rumor dissemination and effectively control the outbreak of epidemics within many real-world systems. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Influential spreaders identification algorithms Classified neighbors Complex networks

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Optimal Parameter identification for a Hydrodynamic Roll Gap Model in Hot Strip Rolling

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IFAC-PapersOnLine 2018年第21期51卷 195-200页

作者： Müller, Martin Steinboeck, Andreas Prinz, Katharina Kugi, Andreas TU WienVienna Austria TU WienVienna Austria

When using modern model-based control concepts in a hot strip rolling mill, an accurate prediction of the roll force is crucial for the achieved control accuracy in terms of the strip thickness. Hence, the influence of various process parameters, e.g., lubrication, on the roll force is of central interest. Commonly used roll gap models are based on the slab method and are often not capable of describing these influences. The hydrodynamic roll gap model, however, can capture the influence of varying friction conditions between the strip and the work rolls. Varying friction conditions can be caused, for instance, by lubrication. This paper presents a combination of the hydrodynamic roll gap model with tailored material models for a more accurate prediction of the roll force in a tandem rolling mill. To parametrize the model, an optimization-based identification algorithm is proposed for unknown friction coefficients and material parameters. The identification algorithm is used on measurement data from an industrial hot strip rolling mill. A comparison with a commonly used roll gap model shows that the parametrized hydrodynamic roll gap model predicts the roll force with significantly higher accuracy. © 2018

关键词： Parameter estimation Friction Hot rolling Hydrodynamics Iron and steel industry Lubrication Rolling mills Steelmaking Strip metal Accurate prediction Friction coefficients Friction conditions Hot strip rolling identification algorithms Model based controls Non linear least squares Roll gap

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Direct Closed-Loop identification Approach to Magnetic Levitation System

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IFAC-PapersOnLine 2018年第15期51卷 610-615页

作者： Sun, Lianming Sano, Akira Liu, Xinyu The University of Kitakyushu 1-1 Hibikino Wakamatsu-ku Kitakyushu Japan Keio University 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan

It is necessary to perform the identification experiment of a magnetic levitation system in closed-loop where the unstable dynamics are stabilized by a feedback controller. However, the identification performance often suffers from the severe numerical problems in the optimization procedure to obtain the unstable property of the levitation system due to the less independent informative components, the poor excitation in the measured signals limited by the low loop's sensitivity to the external signals, the correlation between input-output of the magnetic levitation and the strong noise signal. In this work, a new identification algorithm is developed for the magnetic levitation system. It introduces the output over-sampling scheme to collect the informative input-output data, and uses the subspace characteristics to complement the excitation of the observation data. Furthermore, the new algorithm expresses the updating formula in such a manner that can easily explore the unstable dynamics of the magnetic levitation model. The results of the identification experiment illustrate the identification performance has been improved in the proposed algorithm. © 2018

关键词： Magnetic levitation Nonlinear control systems Closed loop identification Cyclostationarity Direct closed loop identification identification algorithms Magnetic levitation systems Optimization procedures Over sampling subspace

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