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Modulating Function Based Fault Diagnosis Using the Parity Space Method 19

Modulating Function Based Fault Diagnosis Using the Parity S...

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19th ifac symposium on System Identification (SYSID)

作者： Enciso, Luis Noack, Matti Reger, Johann Perez-Zuniga, Gustavo Pontifical Catholic Univ Peru Dept Engn Lima Peru Tech Univ Ilmenau Control Engn Grp Ilmenau Germany

A model-based method for the detection and estimation of faults in dynamic systems is proposed. The method is based on the combination of the parity space approach and the modulating function framework for estimation. The parity space method is employed as an efficient geometric procedure determining null subspaces for annihilating unknown terms and formulating residuals. With the modulating functions technique the dynamic relation from output differentiation is reformulated as an algebraic expression. This substantially reduces the noise sensitivity of the output derivatives required. The design allows for the robust fault detection and isolation also for some nonlinear systems. The robustness of the approach is demonstrated on a nonlinear model of a four-tank process. Copyright (C) 2021 The Authors.

关键词： Modulating Functions Approach Fault Detection Parity Space Method

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Synthesis-Based Engineering of Supervisory controllers for Autonomous Robotic 16th

Synthesis-Based Engineering of Supervisory Controllers for A...

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16th ifac symposium on control in Transportation systems (CTS)

作者： Kok, J. W. Torta, E. Reniers, M. A. Van de Mortel-Fronczak, J. M. van de Molengraft, M. J. G. Eindhoven Univ Technol Eindhoven Netherlands

When mobile robots are employed in transportation tasks involving contact with humans, their control software shall guarantee that in every possible circumstance safety and, in general, task requirements are guaranteed. When control models are manually translated into an executable implementation, it becomes cumbersome to provide such guarantees. Model-driven engineering approaches provide an answer to such a problem. Domain specific models are automatically translated into an executable implementation. Some model-driven engineering approaches exist that are specific to robotics. However, formal guarantees on correctness of the model and the generated implementation with respect to the requirements are, often, not provided. This paper investigates how a general purpose modelling language for supervisory controller synthesis can be used to formally model plants and requirements for a robotic navigation task and can generate an executable implementation that can be integrated into a leading middleware for robotic applications. The starting point is the modelling of the interface provided by existing navigation components available in the targeted middleware. We demonstrate, with simulations and real-life experiments, that the generated supervisory controller is suitable for real-time deployment and guarantees correctness of the model with respect to the requirements of the navigation task at hand. Results on the reaction time of the supervisory controller show that such reaction time is about twenty times smaller than the one of the same supervisory controller implemented with a conventional framework. Copyright (C) 2021 The Authors

关键词： Supervisory controlautomata Autonomous robotic systems Guidance navigation and control Mobile robots Modeling

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Identification of Output-Error Models and an Iterative Optimization Algorithm to Size Fast Ancillary Services for Grid Frequency control 19

Identification of Output-Error Models and an Iterative Optim...

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19th ifac symposium on System Identification (SYSID)

作者： Rapizza, Marco R. Canevese, Silvia M. Ric Sul Sistema Energet RSE SpA I-20134 Milan Italy

The increasing displacement of conventional with renewable power generation, typically non-programmable and endowed with very small or even no rotating inertia, is being accompanied by an increase of the amplitude and speed of grid frequency fluctuations. New control actions are therefore being introduced by grid operators, in the form of fast ancillary services for frequency regulation. An iterative procedure, based on the Gauss-Newton approach, is proposed here to compute the needed quantities of two fast innovative controls, namely fast primary frequency control and synthetic inertia support. In particular, by means of the identification of an output-error model, non-linear behaviours are effectively considered in the computation: dead bands on the frequency measures feeding the controllers;for renewable power plants, downward modulation schemes;for conventional ones, limits on the available control power and limitations on the maximum gradient (time derivative) of the power. The approach is tested by means of simulations in a 2030 predicted scenario for the Sardinian power system. Copyright (C) 2021 The Authors.

关键词： Modeling and simulation of power systems Nonlinear process control Power systems stability Optimal operation and control of power systems Nonlinear identification

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A New Modeling Approach for Stability of Micro/Nano Bubbles 3rd

A New Modeling Approach for Stability of Micro/Nano Bubbles

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3rd ifac Conference on modelling, Identification and control of Nonlinear systems (MiCNON)

作者： Dogan, Mustafa Bunyatova, Ulviya Ferhanoglu, Onur Istanbul Tech Univ Fac Elect Elect Engn Dept Control & Automat Engn TR-34469 Istanbul Turkey Baskent Univ Fac Engn Dept Biomed Engn Baglica Kampusu TR-06790 Ankara Turkey Istanbul Tech Univ Fac Elect Elect Engn Dept Elect & Commun Engn TR-34469 Istanbul Turkey

Microbubbles and nanobubbles have several characteristics that are comparable with millimeter- and centimeter-sized bubbles. These characteristics are their small size, which results in large surface area and high bioactivity, low rising velocity, decreased friction drag, high internal pressure, large gas dissolution capacity, negatively charged surface, and ability to be crushed and form free radicals. controlling and modeling fundamental properties such as nucleation and of the dynamics of these bubbles is key to successfully exploiting their potential in the growing number of applications such as biomedical diagnosis and therapy, antimicrobial in aquaculture, environment, engineering, stock raising and marine industry. Laser-generated bubble dimensions can be characterized with an optical setup employing a high power continuous wave green laser for bubble generation. In this work, non-resonant, self-excited due to structurally nonlinear properties of the hydrogel, bubble formation was modeled as functions of well-controlled parameters of the colloidal media that is multi-layered and anisotropic, engineered uniquely. Copyright (C) 2021 The Authors.

关键词： nano bubbles anisotropic colloidal laser treatment modeling pump-probe

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Bayes control of Hammerstein systems 19

Bayes Control of Hammerstein Systems

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19th ifac symposium on System Identification (SYSID)

作者： Ferizbegovic, Mina Mattsson, Per Schon, Thomas B. Hjalmarsson, Hakan KTH Royal Inst Technol Div Decis & Control Syst Stockholm Sweden Uppsala Univ Dept Informat Technol Uppsala Sweden

In this paper, we consider data driven control of Hammerstein systems. For such systems a common control structure is a transfer function followed by a static output nonlinearity that tries to cancel the input nonlinearity of the system, which is modeled as a polynomial or piece-wise linear function. The linear part of the controller is used to achieve desired disturbance rejection and tracking properties. To design a linear part of the controller, we propose a weighted average risk criterion with the risk being the average of the squared L-2 tracking error. Here the average is with respect to the observations used in the controller and the weighting is with respect to how important it is to have good control for different impulse responses. This criterion corresponds to the average risk criterion leading to the Bayes estimator and we therefore call this approach Bayes control. By parametrizing the weighting function and estimating the corresponding hyperparameters we tune the weighting function to the information regarding the true impulse response contained in the data set available to the user for the control design. The numerical results show that the proposed methods result in stable controllers with performance comparable to the optimal controller, designed using the true input nonlinearity and true plant. Copyright (C) 2021 The Authors.

关键词： Bayesian methods Model reference control Hammerstein system

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Data-driven analysis and control of continuous-time systems under aperiodic sampling 19

Data-driven analysis and control of continuous-time systems ...

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19th ifac symposium on System Identification (SYSID)

作者： Berberich, Julian Wildhagen, Stefan Hertneck, Michael Allgoewer, Frank Univ Stuttgart Inst Syst Theory & Automat Control D-70569 Stuttgart Germany

We investigate stability analysis and controller design of unknown continuous -time systems under state -feedback with aperiodic sampling, using only noisy data but no model knowledge. We first derive a novel data-dependent parametrization of all linear time-invariant continuous -time systems which are consistent with the measured data and the assumed noise bound. Based on this parametrization and by combining tools from robust control theory and the time-delay approach to sampled-data control, we compute lower bounds on the maximum sampling interval (MSI) for closed-loop stability under a given state-feedback gain, and beyond that, we design controllers which exhibit a possibly large MSI. Our methods guarantee the stability properties robustly for all systems consistent with the measured data. As a technical contribution, the proposed approach embeds existing methods for sampled-data control into a general robust control framework, which can be directly extended to model-based robust controller design for uncertain time-delay systems under general uncertainty descriptions. Copyright (C) 2021 The Authors.

关键词： Data-driven control continuous time system estimation

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Identifiability of pharmacological models for online individualization 11th

Identifiability of pharmacological models for online individ...

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11th ifac symposium on Biological and Medical systems (BMS)

作者： Wahlquist, Ylva Gojak, Amina Soltesz, Kristian Lund Univ Dept Automat Control Lund Sweden

There is a large variability between individuals in the response to anesthetic drugs, that seriously limits the achievable performance of closed-loop controlled drug dosing. Full individualization of patient models based on early clinical response data has been suggested as a means to improve performance with maintained robustness (safety). We use estimation theoretic analysis and realization theory to characterize practical identifiability of the standard pharmacological model structure from anesthetic induction phase data and conclude that such approaches are not practically feasible. Copyright (C) 2021 The Authors.

关键词： Individualized anesthesia Drug delivery Identifiability Pharmacokinetic/pharmacodynamic modeling Sensitivity analysis

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Identification of cardiac afterload dynamics from data 11th

Identification of cardiac afterload dynamics from data

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11th ifac symposium on Biological and Medical systems (BMS)

作者： Pigot, Henry Hansson, Jonas Paskevicius, Audrius Liao, Qiuming Sjoberg, Trygve Steen, Stig Soltesz, Kristian Lund Univ Dept Automat Control Lund Sweden Lund Univ Dept Clin Sci Div Thorac Surg Lund Sweden Skane Univ Hosp Dept Cardiothorac Surg Lund Sweden

The prospect of ex vivo functional evaluation of donor hearts is considered. Particularly, the dynamics of a synthetic cardiac afterload model are compared to those of normal physiology. A method for identification of continuous-time transfer functions from sampled data is developed and verified against results from the literature. The method relies on exact gradients and Hessians obtained through automatic differentiation. This also enables straightforward sensitivity analyses. Such analyses reveal that the 4-element Windkessel model is not practically identifiable from representative data while the 3-element model underfits the data. Direct comparison of aortic pressure-flow relations, without relying on matching of fitted Windkessel model parameters, is therefore suggested as an alternative for comparing afterload dynamics. Copyright (C) 2021 The Authors.

关键词： Medical systems Identifiability Windkessel models

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A deep learning framework for light propagation modelling for quantitative photoacoustics

A deep learning framework for light propagation modelling fo...

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IEEE International symposium on Applications of Ferroelectrics (ISAF)

作者： Mengjie Shi Tom Vercauteren Wenfeng Xia Department of Biomedical Engineering and Imaging Sciences King’s College London London UK

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

Photoacoustic (PA) imaging is a hybrid modality based on optical absorption and ultrasound (US) detection. Quantitative PA imaging provides valuable functional information such as blood oxygen saturation, sO 2 , by estimating chromophore concentrations from multispectral PA images. The quantification remains challenging due to unknown light attenuation in heterogeneous tissues. Monte Carlo (MC) simulation is regarded as the gold standard for modelling light propagation in turbid media. It leverages stochastic modelling methods through the simulation of the random walk of photon packets, thus it is computationally demanding and not suitable for real-time applications. In this work, for the first time, we propose a deep learning (DL) framework for light propagation modelling, with a focus on quantitative PA imaging. Compared to the MC simulation, our method reduced the computation time by 4 orders of magnitude, from 33 minutes to 46 milliseconds for a 3D simulation. In addition, the DL-based light fluence estimation improved sO 2 quantification accuracy, achieving an average estimation error of 0.3% with a blood phantom, and showed no significant difference compared to the MC simulation. This framework aims to provide a time-efficient solution for light propagation modelling in turbid media, thereby enhancing the quantification accuracy for real-time PA imaging applications.

关键词： Deep learning Accuracy Ultrasonic imaging Three-dimensional displays Computational modeling Stochastic processes Media Real-time systems Blood Photonics

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Pattern-based Digital Twin for Optimizing Manufacturing systems: A Real Industrial-Case Application 17th

Pattern-based Digital Twin for Optimizing Manufacturing Syst...

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17th ifac symposium on Information control Problems in Manufacturing (INCOM)

作者： Semeraro, Concetta Lezoche, Mario Panetto, Herve Dassisti, Michele Politecn Bari Dept Mech Math & Management DMMM Bari Italy Univ Lorraine CRAN CNRS Nancy France

The digital twin has received strong interests from researchers and industries since it allows predictive manufacturing by integrating the cyber and the physical space. An important prerequisite for the cyber physical integration is a proper and highly -accurate digital model. Considering the complexity of digital modelling, the paper aims at developing and using predefined modelling patterns to enable building digital models independently of the specific application domain The idea is explored and validated on a real case study by designing a set of patterns to create a digital twin model prototype adopted to control and optimize the manufacturing system taken into account. Copyright (C) 2021 The Authors.

关键词： Digital Twin CPS Data-driven modelling Patterns Predictive Manufacturing

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