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UKACC International Conference on control (control)

作者： Muhammad Abdullah John Anthony Rossiter Department of Automatic Control and System Engineering University of Sheffield UK

This work proposes an improved method for Predictive Functional control (PFC) to handle an integrating process. Instead of assuming a constant future input, the dynamic is shaped with a first-order Laguerre polynomial so that it converges to the expected steady state value. This modification provides simpler coding and tuning compared to the conventional method in the literature. Simulation results show that the proposed controller improves the consistency of the open-loop prediction of an integrating process and thus improves closed-loop performance and constraint handling properties. The practicality of this algorithm is also validated on laboratory hardware.

关键词： Prediction algorithms Steady-state Tuning Process control Predictive models Trajectory

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Optimal control of fructo-oligosaccharide production 10

Optimal control of fructo-oligosaccharide production

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10th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2018

作者： Schorsch, J. Kinnaert, M. Fekih-Salem, R. Dewasme, L. Castro, C.C. Vande Wouwer, A. Department of Control Engineering and System Analysis Université libre de Bruxelles Belgium LAMSIN University of Tunis El Manar Tunisia Automatic Control Laboratory University of Mons Belgium Applied Chemistry and Biochemistry Department University of Mons Belgium

ISBN: (纸本)9789492859013

The objective of this study is to determine an optimal substrate feed rate for optimizing the fructo-oligosaccharide production by Aureobasidium pullulans in a fed batch reactor. The feed profile is charecterized by the feed start time, rate and end time. The optimization is carried out based on a simple dynamic model of the process and using Pontryagin maximum principle in the framework of singular control problems. The resulting control law is of the bang-bang type. The bioreactor is first filled-up at maximum feed rate, followed by a batch phase. © 2018 EUROSIS-ETI.

关键词： Substrates

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Extremum Seeking Algorithms based on Non-Commutative Maps

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IFAC-PapersOnLine 2019年第16期52卷 688-693页

作者： Jan Feiling Christophe Labar Victoria Grushkovskaya Emanuele Garone Michel Kinnaert Christian Ebenbauer Institute for Systems Theory and Automatic Control University of Stuttgart Germany Dr. Ing. h.c. F. Porsche AG Stuttgart Germany Department of Control Engineering and System Analysis Université libre de Bruxelles Belgium Institute for Mathematics Julius-Maximilians-University Würzburg Germany

In this work, discrete-time extremum seeking algorithms for unconstrained optimization problems are developed. A general class of non-commutative maps and one- and two point function evaluation polices are presented to approximate a gradient-descent algorithm, suitable for extremum seeking problems. Moreover, adaptive step size rules are discussed to achieve faster convergence and vanishing steady state oscillations.

关键词： Extremum Seeking Optimization Adaptive control Discrete-Time systems

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Sausage, kink, and fluting MHD wave modes identified in solar magnetic pores by Solar Orbiter/PHI

arXiv

引用

arXiv 2024年

作者： Jafarzadeh, S. Schiavo, L.A.C.A. Fedun, V. Solanki, S.K. Stangalini, M. Calchetti, D. Verth, G. Jess, D.B. Grant, S.D.T. Ballai, I. Gafeira, R. Keys, P.H. Fleck, B. Morton, R.J. Browning, P.K. Silva, S.S.A. Appourchaux, T. Gandorfer, A. Gizon, L. Hirzberger, J. Kahil, F. Suárez, D. Orozco Schou, J. Strecker, H. del Toro Iniesta, J.C. Valori, G. Volkmer, R. Woch, J. Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3 Göttingen37077 Germany School of Physics & Astronomy The University of Manchester Oxford Road ManchesterM13 9PL United Kingdom Department of Mathematics Physics and Electrical Engineering Northumbria University Newcastle upon TyneNE1 8ST United Kingdom Plasma Dynamics Group Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom ASI Italian Space Agency Via del Politecnico snc RomeI-00133 Italy Plasma Dynamics Group School of Mathematics and Statistics The University of Sheffield Hicks Building Hounsfield Road SheffieldS3 7RH United Kingdom Astrophysics Research Centre School of Mathematics and Physics Queen’s University Belfast BelfastBT7 1NN United Kingdom Department of Physics and Astronomy California State University Northridge NorthridgeCA91330 United States Instituto de Astrofísica e Ciências do Espaço Department of Physics University of Coimbra Coimbra3040-004 Portugal ESA Science and Operations Department c/o NASA Goddard Space Flight Center GreenbeltMD20771 United States Univ. Paris-Sud Institut d’Astrophysique Spatiale UMR 8617 CNRS Bâtiment 121 Orsay91405 Cedex France Apartado de Correos 3004 GranadaE-18080 Spain Leibniz-Institut für Sonnenphysik Schöneckstr. 6 FreiburgD-79104 Germany Institut für Astrophysik und Geophysik Georg-August-Universität Göttingen Friedrich-Hund-Platz 1 Göttingen37077 Germany

Solar pores are intense concentrations of magnetic flux that emerge through the Sun’s photosphere. When compared to sunspots, they are much smaller in diameter and hence can be impacted and buffeted by neighbouring granular activity to generate significant magnetohydrodynamic (MHD) wave energy flux within their confines. However, observations of solar pores from ground-based telescope facilities may struggle to capture subtle motions synonymous with higher-order MHD wave signatures due to seeing effects produced in the Earth’s atmosphere. Hence, we have exploited timely seeing-free and high-quality observations of four small magnetic pores from the High Resolution Telescope (HRT) of the Polarimetric and Helioseismic Imager (PHI) on board the Solar Orbiter spacecraft, during its first close perihelion passage in March 2022 (at a distance of 0.5 au from the Sun). Through acquisition of data under stable observing conditions, we have been able to measure the area fluctuations and horizontal displacements of the solar pores. Cross correlations between perturbations in intensity, area, line-of-sight velocity, and magnetic fields, coupled with the first-time application of novel Proper Orthogonal Decomposition (POD) techniques on the boundary oscillations, provide a comprehensive diagnosis of the embedded MHD waves as sausage and kink modes. Additionally, the previously elusive m = 2 fluting mode is identified in the most magnetically isolated of the four pores. An important consideration lies in how the identified wave modes contribute towards the transfer of energy into the upper solar atmosphere. We find that the four pores examined have approximately 56%, 72%, 52%, and 34% of their total wave energy associated with the identified sausage modes, and around 23%, 17%, 39%, and 49% to their kink modes, respectively, while the first pore also has around an 11% contribution linked to the fluting mode. This study marks the first-time identification of concurrent sausage, kin

关键词： Magnetohydrodynamics

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A Formal Sensitivity Analysis for Laguerre Based Predictive Functional control 12

A Formal Sensitivity Analysis for Laguerre Based Predictive ...

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UKACC 12th International Conference on control, control 2018

作者： Abdullah, Muhammad Anthony Rossiter, John Department of Automatic Control and System Engineering University of Sheffield Mappin Street SI 3JD United Kingdom Department of Mechanical Engineering International Islamic University Malaysia Jalan Gombak Kuala Lumpur53100 Malaysia

ISBN: (纸本)9781538628645

A Laguerre Predictive Functional control (LPFC) is a simple input shaping method, which can improve the prediction consistency and closed-loop performance of the conventional approach (PFC). However, it is well-known that an input shaping method, in general, will affect the loop sensitivity of a system. Hence, this paper presents a formal sensitivity analysis of LPFC by considering the effect of noise, unmeasured disturbance and parameter uncertainty. Sensitivity plots from bode diagrams and closed-loop simulation are used to illustrate the controller robustness and indicate that although LPFC often provides a better closed-loop tracking response and disturbance rejection, this may involve some trade-off with the sensitivity to noise and parameter uncertainty. Finally, to validate the practicality of the results, the sensitivity of the LPFC control law is illustrated on real-time laboratory hardware. © 2018 IEEE.

关键词： Sensitivity analysis

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Decentralized and Dynamic Fault Detection Using PCA and Bayesian Inference

Decentralized and Dynamic Fault Detection Using PCA and Baye...

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IEEE International Conference on Emerging Technologies and Factory Automation

作者： A. Sanchez-Fernandez M. J. Fuente G. I. Sainz-Palmero Department of System Engineering and Automatic Control EII University of Valladolid Valladolid Spain

This paper proposes a dynamic and decentralized fault detection method. The plant is divided in groups whose members are selected using linear and non-linear modelling techniques. In each group a Principal Component Analysis model does the fault detection, including delayed data to get a dynamic method. Then, a central node fuses the results of each group, using Bayesian Index Criterion (BIC), to get a global detection outcome. The method was tested on a widely used benchmark and compared with other proposal to check its effectiveness.

关键词： Fault detection Dynamic principal component analysis Decentralized process monitoring Decision fusion

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A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners

arXiv

引用

arXiv 2019年

作者： Etxegarai, Urtats Portillo, Eva Irazusta, Jon Koefoed, Lucien Kasabov, Nikola Department of Automatic Control and System Engineering Faculty of Engineering University of the Basque Country UPV/EHU Bilbao Spain Department of Physiology Faculty of Medicine and Nursing University of the Basque Country UPV/EHU Leioa Spain Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

In this work, a heuristic as operational tool to estimate the lactate threshold and to facilitate its integration into the training process of recreational runners is proposed. To do so, we formalize the principles for the lactate threshold estimation from empirical data and an iterative methodology that enables experience based learning. This strategy arises as a robust and adaptive approach to solve data analysis problems. We compare the results of the heuristic with the most commonly used protocol by making a first quantitative error analysis to show its reliability. Additionally, we provide a computational algorithm so that this quantitative analysis can be easily performed in other lactate threshold protocols. With this work, we have shown that a heuristic (%60 of endurance running speed reserve), serves for the same purpose of the most commonly used protocol in recreational runners, but improving its operational limitations of accessibility and consistent use. Copyright © 2019, The Authors. All rights reserved.

关键词： Decision support systems

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Uncertainty propagation in neural networks for sparse coding

arXiv

引用

arXiv 2018年

作者： Kuzin, Danil Isupova, Olga Mihaylova, Lyudmila Department of Automatic Control and System Engineering University of Sheffield United Kingdom Department of Engineering Science University of Oxford United Kingdom

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A Gaussian Process Regression Approach for Fusion of Remote Sensing Images for Oil Spill Segmentation

A Gaussian Process Regression Approach for Fusion of Remote ...

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International Conference on Information Fusion

作者： Fodio S Longman Lyudmila Mihaylova Le Yang Department of Automatic Control and System Engineering University of Sheffield UK Department of Electrical and Computer Engineering University of Canterbury Chrischurch New Zealand

Synthetic Aperture Radar (SAR) satellite systems are very efficient in oil spill monitoring due to their capability to operate under all weather conditions. This paper presents a framework using Gaussian process (GP) to fuse SAR images of different modalities and to segment dark areas (assumed oil spill) for oil spill detection. A new covariance function; a product of an intrinsically sparse kernel and a Rational Quadratic Kernel (RQK) is used to model the prior of the estimated image allowing information to be transferred. The accuracy performance evaluation demonstrates that the proposed framework has 37% less RMSE per pixel and a compelling enhancement visually when compared with existing methods.

关键词： Oils Kernel Synthetic aperture radar Image resolution Gaussian processes Feature extraction Image segmentation

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The NRSF-SVM based method for nonlinear rotor bearing fault diagnosis

The NRSF-SVM based method for nonlinear rotor bearing fault ...

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第30届中国控制与决策会议

作者： Ying Ma Zhong Luo Haopeng Liu Yunpeng Zhu School of Mechanical Engineering & Automation Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Department of Automatic Control and System Engineering University of Sheffield

The fault diagnosis scheme of the rotor bearing system often conducted by using either signal analysis approach or modeling method. In practice, the structure of the rotor bearing system is complex and contains many nonlinear factors. Therefore, it is hard to use the model-based method for fault detection. Thus, signal analysis approach is more efficient. In the signal analysis approach, frequency response function is widely applied. However, the existing analyzing methods of frequency response function have some limitations, such as multidimensional property. Thus, in this study, the concept of Nonlinear Response Spectrum Function(NRSF) is proposed to solve the problem. Finally, a simulation is conducted to identify the multi-fault rotor bearing systems by the proposed NRSFs feature and Support Vector Machine(SVM) classifier, showing that the NRSF-SVM approach has an excellent performance in fault identification of rotor bearing system.

关键词： rotor bearing system fault diagnosis NRSF SVM

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