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Articles de revues sur le sujet « Real-time model order reduction »

Auteur : Grafiati

Publié le 8 mars 2025

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1

SUZUKI, Katsuyuki, Masaru OKAYASU et Ryuta OKADA. « 1803 Real Time Large Deformation Simulation using Model Order Reduction ». Proceedings of The Computational Mechanics Conference 2013.26 (2013) : _1803–1_—_1803–3_. http://dx.doi.org/10.1299/jsmecmd.2013.26._1803-1_.

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Dams, Dennis, Rob Gerth, Bart Knaack et Ruurd Kuiper. « Partial-order Reduction Techniques for Real-time Model Checking ». Formal Aspects of Computing 10, n^o 5-6 (26 mai 1998) : 469–82. http://dx.doi.org/10.1007/s001650050028.

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Frank, Tobias, Henrik Zeipel, Mark Wielitzka, Steffen Bosselmann et Tobias Ortmaier. « Real-Time Prediction of Curing Processes using Model Order Reduction ». IFAC-PapersOnLine 53, n^o 2 (2020) : 11132–37. http://dx.doi.org/10.1016/j.ifacol.2020.12.273.

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Far, Mehrnaz Farzam, Floran Martin, Anouar Belahcen, Paavo Rasilo et Hafiz Asad Ali Awan. « Real-Time Control of an IPMSM Using Model Order Reduction ». IEEE Transactions on Industrial Electronics 68, n^o 3 (mars 2021) : 2005–14. http://dx.doi.org/10.1109/tie.2020.2973901.

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5

Nasika, Christina, Pedro Díez, Pierre Gerard, Thierry J. Massart et Sergio Zlotnik. « Towards real time assessment of earthfill dams via Model Order Reduction ». Finite Elements in Analysis and Design 199 (février 2022) : 103666. http://dx.doi.org/10.1016/j.finel.2021.103666.

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González, David, Alberto Badías, Icíar Alfaro, Francisco Chinesta et Elías Cueto. « Model order reduction for real-time data assimilation through Extended Kalman Filters ». Computer Methods in Applied Mechanics and Engineering 326 (novembre 2017) : 679–93. http://dx.doi.org/10.1016/j.cma.2017.08.041.

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Vettermann, J., S. Sauerzapf, A. Naumann, M. Beitelschmidt, R. Herzog, P. Benner et J. Saak. « MODEL ORDER REDUCTION METHODS FOR COUPLED MACHINE TOOL MODELS ». MM Science Journal 2021, n^o 3 (30 juin 2021) : 4652–59. http://dx.doi.org/10.17973/mmsj.2021_7_2021072.

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Thermal effects are the most dominant source for displacements in machine tools and thus work-piece inaccuracies during the manufacturing process. A promising strategy to meet the ever-increasing accuracy requirements is the use of predictive models for, e.g., parameter and design op-timizations or online correction of the thermally induced error at the tool center point (TCP) in the pro-duction process. However, these techniques require fast but precise simulations. The need for high model accuracy is in direct contrast to the desired real-time capabilities. Model order reduction (MOR) is an attractive tool to overcome this problem. A modeling toolchain, which is tailored for the effective construction of fast and accurate models is proposed and demonstrated, emphasizing the involved MOR step.

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Kiss, Kristóf Levente, et Tamás Orosz. « Model Order Reduction Methods for Rotating Electrical Machines : A Review ». Energies 17, n^o 20 (16 octobre 2024) : 5145. http://dx.doi.org/10.3390/en17205145.

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Due to the rise of e-mobility applications, there is an increased demand to create more accurate control methods, which can reduce the loss in an e-drive system. The accurate modeling of the rotating machines needs to resolve a partial differential equation system that describes the thermal and mechanical behavior of the different parts in addition to the electromagnetic design. Due to these models’ limited resources and high computation demand, they cannot be used directly for real-time control. Model order reduction methods have been of growing interest in the past decades and offer solutions for this problem. According to the processed literature, many model order reduction-based methods are used for a wide range of problems. However, a paper has not been published that discusses a model order reduction-based real-time control model that is actually used in the industry. This paper aims to summarize and systematically review the model order reduction methods developed for rotating electrical machines in the last two decades and examine the possible usage of these methods for a real-time control problem.

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SUZUKI, Katsuyuki, Masayuki WADA et Masaru OKAYASU. « 2304 Real Time Simulation of Dynamic Large Deformation Problem using Model Order Reduction ». Proceedings of The Computational Mechanics Conference 2012.25 (2012) : 571–73. http://dx.doi.org/10.1299/jsmecmd.2012.25.571.

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ALDHAHERI, RABAH W. « Model order reduction via real Schur-form decomposition ». International Journal of Control 53, n^o 3 (mars 1991) : 709–16. http://dx.doi.org/10.1080/00207179108953642.

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Shamisa, Abdolah, Babak Majidi et Jagdish C. Patra. « Sliding-Window-Based Real-Time Model Order Reduction for Stability Prediction in Smart Grid ». IEEE Transactions on Power Systems 34, n^o 1 (janvier 2019) : 326–37. http://dx.doi.org/10.1109/tpwrs.2018.2868850.

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Goyal, Pawan, et Martin Redmann. « Time-limited H2-optimal model order reduction ». Applied Mathematics and Computation 355 (août 2019) : 184–97. http://dx.doi.org/10.1016/j.amc.2019.02.065.

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Buchfink, Patrick, Ashish Bhatt et Bernard Haasdonk. « Symplectic Model Order Reduction with Non-Orthonormal Bases ». Mathematical and Computational Applications 24, n^o 2 (21 avril 2019) : 43. http://dx.doi.org/10.3390/mca24020043.

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Parametric high-fidelity simulations are of interest for a wide range of applications. However, the restriction of computational resources renders such models to be inapplicable in a real-time context or in multi-query scenarios. Model order reduction (MOR) is used to tackle this issue. Recently, MOR is extended to preserve specific structures of the model throughout the reduction, e.g., structure-preserving MOR for Hamiltonian systems. This is referred to as symplectic MOR. It is based on the classical projection-based MOR and uses a symplectic reduced order basis (ROB). Such an ROB can be derived in a data-driven manner with the Proper Symplectic Decomposition (PSD) in the form of a minimization problem. Due to the strong nonlinearity of the minimization problem, it is unclear how to efficiently find a global optimum. In our paper, we show that current solution procedures almost exclusively yield suboptimal solutions by restricting to orthonormal ROBs. As a new methodological contribution, we propose a new method which eliminates this restriction by generating non-orthonormal ROBs. In the numerical experiments, we examine the different techniques for a classical linear elasticity problem and observe that the non-orthonormal technique proposed in this paper shows superior results with respect to the error introduced by the reduction.

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Radić-Weissenfeld, Lj, S. Ludwig, W. Mathis et W. John. « Model order reduction of linear time invariant systems ». Advances in Radio Science 6 (26 mai 2008) : 129–32. http://dx.doi.org/10.5194/ars-6-129-2008.

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Abstract. This paper addresses issues related to the order reduction of systems with multiple input/output ports. The order reduction is divided up into two steps. The first step is the standard order reduction method based on the multipoint approximation of system matrices by applying Krylov subspace. The second step is based on the rejection of the weak part of a system. To recognise the weak system part, Lyapunov equations are used. Thus, this paper introduces efficient solutions of the Lyapunov equations for port to port subsystems.

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Padhy, Aditya Prasad, Varsha Singh et Vinay Pratap Singh. « Model order reduction of discrete time uncertain system ». Journal of Information and Optimization Sciences 41, n^o 2 (17 février 2020) : 661–68. http://dx.doi.org/10.1080/02522667.2020.1733200.

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Ritschel, Tobias K. S., Frances Weiß, Manuel Baumann et Sara Grundel. « Nonlinear model reduction of dynamical power grid models using quadratization and balanced truncation ». at - Automatisierungstechnik 68, n^o 12 (18 novembre 2020) : 1022–34. http://dx.doi.org/10.1515/auto-2020-0070.

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AbstractIn this work, we present a nonlinear model reduction approach for reducing two commonly used nonlinear dynamical models of power grids: the effective network (EN) model and the synchronous motor (SM) model. Such models are essential in real-time security assessments of power grids. However, as power grids are often large-scale, it is necessary to reduce the models in order to utilize them in real-time. We reformulate the nonlinear power grid models as quadratic systems and reduce them using balanced truncation based on approximations of the reachability and observability Gramians. Finally, we present examples involving numerical simulation of reduced EN and SM models of the IEEE 57 bus and IEEE 118 bus systems.

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Rydel, Marek, Rafał Stanisławski, Krzysztof J. Latawiec et Marcin Gałek. « Model order reduction of commensurate linear discrete-time fractional-order systems ». IFAC-PapersOnLine 51, n^o 1 (2018) : 536–41. http://dx.doi.org/10.1016/j.ifacol.2018.05.090.

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Tsokanas, N., T. Simpson, R. Pastorino, E. Chatzi et B. Stojadinović. « Model order reduction for real-time hybrid simulation : Comparing polynomial chaos expansion and neural network methods ». Mechanism and Machine Theory 178 (décembre 2022) : 105072. http://dx.doi.org/10.1016/j.mechmachtheory.2022.105072.

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Son, Nguyen Thanh. « A real time procedure for affinely dependent parametric model order reduction using interpolation on Grassmann manifolds ». International Journal for Numerical Methods in Engineering 93, n^o 8 (5 septembre 2012) : 818–33. http://dx.doi.org/10.1002/nme.4408.

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Xiao, Zhi-Hua, et Yao-Lin Jiang. « Multi-order Arnoldi-based model order reduction of second-order time-delay systems ». International Journal of Systems Science 47, n^o 12 (7 mai 2015) : 2925–34. http://dx.doi.org/10.1080/00207721.2015.1042087.

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Rahman, Sk, Omer San et Adil Rasheed. « A Hybrid Approach for Model Order Reduction of Barotropic Quasi-Geostrophic Turbulence ». Fluids 3, n^o 4 (31 octobre 2018) : 86. http://dx.doi.org/10.3390/fluids3040086.

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We put forth a robust reduced-order modeling approach for near real-time prediction of mesoscale flows. In our hybrid-modeling framework, we combine physics-based projection methods with neural network closures to account for truncated modes. We introduce a weighting parameter between the Galerkin projection and extreme learning machine models and explore its effectiveness, accuracy and generalizability. To illustrate the success of the proposed modeling paradigm, we predict both the mean flow pattern and the time series response of a single-layer quasi-geostrophic ocean model, which is a simplified prototype for wind-driven general circulation models. We demonstrate that our approach yields significant improvements over both the standard Galerkin projection and fully non-intrusive neural network methods with a negligible computational overhead.

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22

Pati, Avadh, Awadhesh Kumar et Dinesh Chandra. « Suboptimal Control Using Model Order Reduction ». Chinese Journal of Engineering 2014 (3 février 2014) : 1–5. http://dx.doi.org/10.1155/2014/797581.

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A Padé approximation based technique for designing a suboptimal controller is presented. The technique uses matching of both time moments and Markov parameters for model order reduction. In this method, the suboptimal controller is first derived for reduced order model and then implemented for higher order plant by partial feedback of measurable states.

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23

Zulfiqar, Umair, Victor Sreeram et Xin Du. « Time-limited pseudo-optimal H 2 -model order reduction ». IET Control Theory & ; Applications 14, n^o 14 (24 septembre 2020) : 1995–2007. http://dx.doi.org/10.1049/iet-cta.2019.1105.

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24

Michiels, Wim, Elias Jarlebring et Karl Meerbergen. « Krylov-Based Model Order Reduction of Time-delay Systems ». SIAM Journal on Matrix Analysis and Applications 32, n^o 4 (octobre 2011) : 1399–421. http://dx.doi.org/10.1137/100797436.

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25

Vishwakarma, C. B., et R. Prasad. « Time domain model order reduction using Hankel matrix approach ». Journal of the Franklin Institute 351, n^o 6 (juin 2014) : 3445–56. http://dx.doi.org/10.1016/j.jfranklin.2014.02.005.

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Birouche, Abderazik, Benjamin Mourllion et Michel Basset. « Model order-reduction for discrete-time switched linear systems ». International Journal of Systems Science 43, n^o 9 (septembre 2012) : 1753–63. http://dx.doi.org/10.1080/00207721.2011.554911.

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Z. Abidin, Z. F., et M. N. Osman Zahid. « Real time object customization in CAD system ». Indonesian Journal of Electrical Engineering and Computer Science 15, n^o 2 (1 août 2019) : 1066. http://dx.doi.org/10.11591/ijeecs.v15.i2.pp1066-1075.

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Object customization in Computer Aided Design (CAD) is a method used to modify the sketch parameters and change the model geometries. This method is one of important features in part modelling which empowered CAD user to simply modify their product. The conventional method of modifying CAD model is usually relied on the manual editing. This paper outlines a development of program than can be integrated in CAD/CAM system for real time object customization. It uses Visual Basic (VB) programming with custom Graphical User Interface (GUI) generated in NX10 (CAD/CAM software) interface. The main contribution of this research is a tool for real time object customization that capable to assist the modification of 3D model. In order to develop the tool, 3D model modification instructions are translated into programming codes by using Journaling tools in NX interface. Editable parameters are identified based on the model shapes. The related codes are reconstructed, modified and linked to the functional GUI. This allows user to simply modify the model shapes in real time with minimum process steps. The performance of the method is evaluated in terms of the reduction of process steps and time in modifying the 3D model in CAD system. All the findings and details of approach are presented.

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Jakani, Anass, Raphael Sommet, Frédérique Simbélie et Jean-Christophe Nallatamby. « Understanding the Thermal Time Constants of GaN HEMTs through Model Order Reduction Technique ». Electronics 10, n^o 24 (16 décembre 2021) : 3138. http://dx.doi.org/10.3390/electronics10243138.

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This paper described a comparison between a numerical Finite Element Analysis (FEA) and an analytical approach in order to extract the thermal time constants and the thermal resistances of simple but realistic structures. Understanding the complex contribution of multidimensional thermal spreading, the effect of multiple layers, and the correlation with the heat source length is mandatory due to the severe mismatch of thermal expansion in different epitaxial layers and high operating temperatures. This is especially true on GaN HEMT (High Electron Mobility Transistor) with the continuous decrease of the gate length and the increase of the power density. Moreover, in this paper, we extracted the time constants with a Model Order Reduction (MOR) technique based on the Ritz vector approach with inputs coming from the FE matrices. It was found that the time constants obtained by an analytical solution and a model order extraction from FEA were exactly the same. This result validated the idea that our MOR technique provides the real time constants and resistances for our device structures and in this case unified the analytical world with the numerical one.

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Uhlmann, E. Prof, T. Prof Reis, O. Rendel et S. Guhde. « Zeitdiskretes echtzeitfähiges Berechnungsmodell*/Time-discrete and real-time modelling - Generation of low-dimensional time-discrete models for high dynamic machine tools ». wt Werkstattstechnik online 107, n^o 07-08 (2017) : 480–86. http://dx.doi.org/10.37544/1436-4980-2017-07-08-4.

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Der Fachbeitrag beschreibt die Ergebnisse für eine automatisierte und anwendungsangepasste Bereitstellung zeitdiskreter deterministischer reduzierter Systeme für das dynamische Verhalten von Werkzeugmaschinen. Dazu wurde ein neuartiges Modellreduktionsverfahren innerhalb eines von der DFG geförderten Grundlagenprojekts entwickelt. Es liefert für eine festgelegte Zeitschrittweite eine niedrigdimensionale Approximation des Originalmodells mit zugehöriger Fehlerabschätzung und unter Beibehaltung inhärenter Systemeigenschaften (Passivität, stationäre Genauigkeit).   This article presents results of a new discrete-time and deterministic reduced model-order systems for dynamic behaviours of machine tools. The developed model-order-reduction method use fixed time steps and was funded by the German Research Foundation (DFG). The time steps provide a low-dimensional approximation of the original model with an associated estimated error. Furthermore the inherent system properties (passivity, steady-state accuracy) are maintained.

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Wu, Fei, Lai Yuan, Aonan Wu et Zhengrui Zhang. « Classification Model for Real-Time Monitoring of Machining Status of Turned Workpieces ». Processes 12, n^o 7 (17 juillet 2024) : 1505. http://dx.doi.org/10.3390/pr12071505.

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The occurrence of tool chatter can have a detrimental impact on the quality of the workpiece. In order to improve surface quality, machining stability, and reduce tool wear cycles, it is essential to monitor the workpiece machining process in real time during the turning process. This paper presents a tool chatter state recognition model based on a denoising autoencoder (DAE) for feature dimensionality reduction and a bidirectional long short-term memory (BiLSTM) network. This study examines the feature dimensionality reduction method of the DAE, whereby the reduced-dimensional data are concatenated and input into the BiLSTM model for training. This approach reduces the learning difficulty of the network and enhances its anti-interference capability. Turning experiments were conducted on a SK50P lathe to collect the dataset for model performance validation. The experimental results and analysis indicate that the proposed DAE-BiLSTM model outperforms other models in terms of prediction and classification accuracy in distinguishing between stable machining, over-machining, and severe chatter stages in turning chatter state recognition. The overall classification accuracy reached 96.28%.

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Dung, Nguyễn Thùy, Nguyễn Thanh Tùng, Vũ Ngọc Kiên et Đào Huy Du. « STOCHASTIC POSITIVE-REAL BALANCED TRUNCATION : A NOVEL MODEL ORDER REDUCTION TECHNIQUE ». TNU Journal of Science and Technology 228, n^o 15 (6 novembre 2023) : 150–56. http://dx.doi.org/10.34238/tnu-jst.8931.

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Trong bối cảnh của cuộc cách mạng số hóa, việc phát triển các kỹ thuật giảm bậc mô hình cho mạch điện, điện tử là vấn đề cấp thiết. Trong bài báo này, chúng tôi giới thiệu một thuật toán mới gọi là Stochastic Positive-Real Balanced Truncation (SPBT) dựa trên sự kết hợp của hai kỹ thuật Cắt ngắn cân bằng thực dương (PRR) và Cắt ngắn cân bằng ngẫu nhiên (SBR) để giảm bậc mô hình. Từ kết quả thử nghiệm và so sánh SPBT với các phương pháp PRR và SBR trên mô hình mạch điện tử, cho thấy SPBT không chỉ bảo toàn tính ổn định, sự thụ động và cực tiểu pha của hệ gốc mà còn mang lại hiệu suất và độ chính xác cao hơn so với PRR và SBR. Với sai số nhỏ, sự trùng khớp về đáp ứng giữa hệ giảm bậc và hệ gốc khi áp dụng SPBT trong miền thời gian và miền tần số, phương pháp này hứa hẹn là một công cụ hiệu quả trong việc giảm độ phức tạp mà vẫn duy trì tính chất vật lý quan trọng của hệ thống.

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Haider, Shafiq, Abdul Ghafoor, Muhammad Imran et Fahad Mumtaz Malik. « Time-limited Gramians-based model order reduction for second-order form systems ». Transactions of the Institute of Measurement and Control 41, n^o 8 (15 octobre 2018) : 2310–18. http://dx.doi.org/10.1177/0142331218798893.

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A new scheme for model order reduction of large-scale second-order systems in time-limited intervals is presented. Time-limited Gramians that are solutions of continuous-time algebraic Lyapunov equations for second-order form systems are introduced. Time-limited second-order balanced truncation procedures with provision of balancing position and velocity Gramians are formulated. Stability conditions for reduced-order models are stated and algorithms that preserve stability in reduced-order models are discussed. Numerical examples are presented to validate the superiority of the proposed scheme compared with the infinite-time Gramians technique for time-limited applications.

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Guillet, Jérôme, Benjamin Mourllion, Abderazik Birouche et Michel Basset. « Extracting second-order structures from single-input state-space models : Application to model order reduction ». International Journal of Applied Mathematics and Computer Science 21, n^o 3 (1 septembre 2011) : 509–19. http://dx.doi.org/10.2478/v10006-011-0039-5.

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Extracting second-order structures from single-input state-space models: Application to model order reductionThis paper focuses on the model order reduction problem of second-order form models. The aim is to provide a reduction procedure which guarantees the preservation of the physical structural conditions of second-order form models. To solve this problem, a new approach has been developed to transform a second-order form model from a state-space realization which ensures the preservation of the structural conditions. This new approach is designed for controllable single-input state-space realizations with real matrices and has been applied to reduce a single-input second-order form model by balanced truncation and modal truncation.

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Park, Yeon-Jeong, et Joon-Ho Cho. « Optimized Controller Design Using Hybrid Real-Time Model Identification with LSTM-Based Adaptive Control ». Applied Sciences 15, n^o 4 (18 février 2025) : 2138. https://doi.org/10.3390/app15042138.

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Most of the processes with various dynamic characteristics can be reduced to the Second Order Plus Time Delay (SOPTD) model by using the model reduction method. We propose a novel hybrid approach that combines Long Short-Term Memory (LSTM)-based real-time model identification with Genetic Algorithms to enhance the Smith predictor control structure. This method compensates for the delay time of the SOPTD model while minimizing the Integral Time Absolute Error performance index. Our approach integrates an optimally adaptive Proportional–Integral–Derivative (PID) controller design algorithm that estimates the coefficients of the SOPTD model in the Smith Predictor control structure and adjusts the PID controller parameters dynamically. The method is improved through a combination of numerical calculation, Genetic Algorithms, and LSTM networks, showing approximately 15% better performance compared to conventional methods. The system demonstrates significant improvements in both performance metrics and resource utilization, including a 40% reduction in execution time and enhanced resource efficiency. Simulation results show that the proposed scheme exhibits improved adaptability to disturbances and process variations, with faster response times and reduced overshoots compared to traditional methods. The steady-state response of the higher-order model and the reduced model shows perfect matching for the unit feedback input.

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Du, Xin, Feibing Fan, Da-Wei Ding et Fuwei Liu. « Finite-frequency model order reduction of discrete-time linear time-delayed systems ». Nonlinear Dynamics 83, n^o 4 (27 novembre 2015) : 2485–96. http://dx.doi.org/10.1007/s11071-015-2496-0.

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Tanji, Yuichi, et Ken'ichi Fujimoto. « Nonlinear model order reduction of continuous-time image reconstruction systems ». Nonlinear Theory and Its Applications, IEICE 12, n^o 3 (2021) : 512–25. http://dx.doi.org/10.1587/nolta.12.512.

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Zhang, Yujie, et Yangfeng Su. « A memory-efficient model order reduction for time-delay systems ». BIT Numerical Mathematics 53, n^o 4 (16 juillet 2013) : 1047–73. http://dx.doi.org/10.1007/s10543-013-0439-z.

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Wang, Xiang, Zheng Zhang, Qing Wang et Ngai Wong. « Gramian-based model order reduction of parameterized time-delay systems ». International Journal of Circuit Theory and Applications 42, n^o 7 (18 décembre 2012) : 687–706. http://dx.doi.org/10.1002/cta.1884.

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Zulfiqar, Umair, Xin Du, Qiu-Yan Song et Victor Sreeram. « On frequency- and time-limited μH2-optimal model order reduction ». Automatica 153 (juillet 2023) : 111012. http://dx.doi.org/10.1016/j.automatica.2023.111012.

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Goury, Olivier, Bruno Carrez et Christian Duriez. « Real-Time Simulation for Control of Soft Robots With Self-Collisions Using Model Order Reduction for Contact Forces ». IEEE Robotics and Automation Letters 6, n^o 2 (avril 2021) : 3752–59. http://dx.doi.org/10.1109/lra.2021.3064247.

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Cheng, Gao-Yuan, Zhen Miao et Yao-Lin Jiang. « High-order Krylov subspace model order reduction methods for bilinear time-delay systems ». Systems & ; Control Letters 186 (avril 2024) : 105764. http://dx.doi.org/10.1016/j.sysconle.2024.105764.

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Casciati, Fabio, et Lucia Faravelli. « Model Order Reduction Issues for Integrated Structural Control Design ». Advances in Science and Technology 83 (septembre 2012) : 37–48. http://dx.doi.org/10.4028/www.scientific.net/ast.83.37.

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Model Order Reduction (MOR) denotes the theory by which one tries to catch a model of order lower than that of the real model, in view of the design of an efficient structural control scheme. When the nonlinear response of the reference structural system affects the nature of the reduced model making it dependent on the visited subset of the input-output space, standard MOR techniques do not apply. The mathematical theory offers some specific alternatives. One of them is applied, in this paper, to a case study focused on a multi-bay, multi-storey plane frame with assigned locations for the potential plastic hinges.

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Jørgensen, Michael, Wolfgang Schilling et Poul Harremoës. « General assessment of potential CSO reduction by means of real time control ». Water Science and Technology 32, n^o 1 (1 juillet 1995) : 249–57. http://dx.doi.org/10.2166/wst.1995.0056.

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A number of case studies have been carried out in which the potential reduction of combined sewer overflows (CSO) by means of real time control (RTC) is assessed for existing sewer systems. It is an inherent problem of case studies that results cannot necessarily be generalized. In this paper results of a systematic investigation of hypothetical combined sewer systems are presented. The systems were characterized in terms of their topological structure, size, type and arrangement of storage and transport elements. The RTC optimization model LOCUS was applied to simulate the performance of local control and of optimum control strategies. The results are expressed as “CSO reduction achieved by optimum control, compared to the locally controlled system”. General conclusions are drawn with respect to possible CSO reduction for a system with given topology, storage and transport characteristics. Finally, these are compared to some case studies reported in the literature in order to verify and show the general applicability of the findings.

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Banagaaya, N., W. H. A. Schilders, G. Alì et C. Tischendorf. « Index-aware model order reduction : LTI DAEs in electric networks ». COMPEL : The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 33, n^o 4 (1 juillet 2014) : 1123–44. http://dx.doi.org/10.1108/compel-12-2012-0362.

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Purpose – Model order reduction (MOR) has been widely used in the electric networks but little has been done to reduce higher index differential algebraic equations (DAEs). The paper aims to discuss these issues. Design/methodology/approach – Most methods first do an index reduction before reducing a higher DAE but this can lead to a loss of physical properties of the system. Findings – The paper presents a MOR method for DAEs called the index-aware MOR (IMOR) which can reduce a DAE while preserving its physical properties such as the index. The feasibility of this method is tested on real-life electric networks. Originality/value – MOR has been widely used to reduce large systems from electric networks but little has been done to reduce higher index DAEs. Most methods first do an index reduction before reducing a large system of DAEs but this can lead to a loss of physical properties of the system. The paper presents a MOR method for DAEs called the IMOR which can reduce a DAE while preserving its physical properties such as the index. The feasibility of this method is tested on real-life electric networks.

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Kleyman, Viktoria, Hannes Gernandt, Karl Worthmann, Hossam S. Abbas, Ralf Brinkmann et Matthias A. Müller. « Modeling and parameter identification for real-time temperature controlled retinal laser therapies ». at - Automatisierungstechnik 68, n^o 11 (26 novembre 2020) : 953–66. http://dx.doi.org/10.1515/auto-2020-0074.

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AbstractLaser photocoagulation is a widely used treatment for a variety of retinal diseases. Temperature-controlled irradiation is a promising approach to enable uniform heating, reduce the risks of over- or undertreatment, and unburden the ophthalmologists from a time consuming manual power titration. In this paper, an approach is proposed for the development of models with different levels of detail, which serve as a basis for improved, more accurate observer and control designs. To this end, we employ a heat diffusion model and propose a suitable discretization and subsequent model reduction procedures. Since the absorption of the laser light can vary strongly at each irradiation site, a method for identifying the absorption coefficient is presented. To identify a parameter in a reduced order model, an optimal interpolatory projection method for parametric systems is used. In order to provide an online identification of the absorption coefficient, we prove and exploit monotonicity of the parameter influence.

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Moreno, Higuatzi, et Alexander Schaum. « Low-Order Electrochemical State Estimation for Li-Ion Batteries ». Algorithms 16, n^o 2 (28 janvier 2023) : 73. http://dx.doi.org/10.3390/a16020073.

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Batteries are complex systems involving spatially distributed microscopic mechanisms on different time scales whose adequate interplay is essential to ensure a desired functioning. Describing these phenomena yields nonlinearly coupled partial differential equations whose numerical solution requires considerable effort and computation time, making it an infeasible solution for real-time applications. Anyway, having information about the internal electrochemical states of the battery can pave the way for many different advanced monitoring and control strategies with a big potential for improving efficiency and longevity. For such purposes, in the present paper, a combination of a low-order representation of the essential dynamics associated to the internal electrochemical mechanisms based on Dynamic Mode Decomposition for control (DMDc) is proposed to obtain an improved equivalent circuit model (ECM) representation with continuously updated parameters and combined with an extended Kalman Filter (EKF). The model-order reduction step extensively exploits the model structure, yielding a well structured low-order representation without artificial numerical correlations. The performance of the proposed method is illustrated with numerical simulations based on a well-established reference model, showing its potential usefulness in real-time applications requiring knowledge of the internal electrochemical states besides the state-of-charge.

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Padhy, A. P., V. Singh et V. P. Singh. « Model Order Reduction of Discrete Time Interval System Based on Time Moment Matching ». Automatic Control and Computer Sciences 55, S1 (décembre 2021) : 77–88. http://dx.doi.org/10.3103/s0146411621090066.

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Li, Yanpeng, Yaolin Jiang et Ping Yang. « Time domain model order reduction of discrete-time bilinear systems with Charlier polynomials ». Mathematics and Computers in Simulation 190 (décembre 2021) : 905–20. http://dx.doi.org/10.1016/j.matcom.2021.06.021.

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Wang, Zhao-Hong, Yao-Lin Jiang et Kang-Li Xu. « Time domain and frequency domain model order reduction for discrete time-delay systems ». International Journal of Systems Science 51, n^o 12 (2 juillet 2020) : 2134–49. http://dx.doi.org/10.1080/00207721.2020.1785578.

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Jiang, Yao-Lin, Jun-Man Yang et Kang-Li Xu. « Model order reduction for discrete-time linear systems with the discrete-time polynomials ». Japan Journal of Industrial and Applied Mathematics 36, n^o 3 (26 août 2019) : 1005–20. http://dx.doi.org/10.1007/s13160-019-00384-0.

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