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第24届中国控制与决策会议

作者： Matej Polka Sergej elikovsky Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in PragueCzech Republic Institute of Information Theory and Automation Prague Czech Republic

A fermentation process is generally defined as a biological process containing the growth of the biomass (bacteria, yeasts) resulting from the consumption of essential substrate supplies (source of carbon, nitrogen, oxygen, etc.). The biomass growth is usually followed by the production of various products from which especially the variety of antibiotics makes the fermentation processes attractive for the industrial utilization. However, the complicated dynamics, high level of uncertainty and nonlinearity and difficult online measurement of the process variables come hand in hand with the attractivity and turn the attempts on optimal control of the fermentation process into a very delicate challenge. To tackle it, the theory of the gradient projection method has been partially adapted and fully implemented by the authors of this paper. Numerical experiments show its significantly better performance than for other known methods. Moreover, these experiments reveal an interesting "superprofile" visible for long cultivation times.

关键词： Fermentation process, penicillin, gradient method, optimization

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Discrete-to-continuous dynamics reconstruction for bilinear systems

Discrete-to-continuous dynamics reconstruction for bilinear ...

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IEEE Conference on Decision and control

作者： Philipp Rumschinski Dina Shona Laila Rolf Findeisen Institute for Automation Engineering System and Control Laboratory Otto-von-Guericke University of Magdeburg Magdeburg Germany Faculty of Engineering and the Environment University of Southampton UK

In this work, we study the reconstruction of continuous-time models from discrete-time models of bilinear systems. Many dynamical systems contain nonlinearities and evolve continuously in time. However, due to the use of digital sensors for data acquisition, system identification methods typically rely on sampled data and yield a discrete-time model. Linking such a discrete-time model to its equivalent continuous-time dynamics is nontrivial. This paper proposes a discrete-to-continuous dynamics reconstruction for discrete-time models of a class of bilinear systems obtained by system identification. We show that for bilinear systems we can obtain a discrete-time model that is consistent with the measurement data. Furthermore, we show that one can derive from the discrete-time model, its equivalent continuous-time model. Two examples illustrate the approach.

关键词： Nonlinear systems Parameter estimation Data models Linear systems Numerical models Vectors Time measurement

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Expansion of the available use classes in IEEE 802.15.4 networks for usage in the industrial environment

Expansion of the available use classes in IEEE 802.15.4 netw...

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2012 9th International Symposium on Wireless Communication Systems, ISWCS 2012

作者： Valle, Odilson T. Montez, Carlos Portugal, Paulo Vasques, Francisco Costa, Daniel G. Federal Institute of Santa Catarina Campus São José Brazil Department of Control and Automation Federal University of Santa Catarina Brazil ISR/IDMEC Faculty of Engineering University of Porto Portugal Department of Technology State University of Feira de Santana Brazil

ISBN: (纸本)9781467307604

The usage of Wireless Sensor Networks (WSNs) in industrial environments has been steadily increasing, due to the reduced deployment and maintenance costs, when compared to the use of wired networks for connecting single I/O points in industrial applications. The most promising WSN standard is the one defined by the IEEE 802.15.4 standard. However, it does not support the adequate mechanisms to deal with the unreliable nature of an industrial communication environment. In this paper, we propose an extension of the use classes available for this standard, together with the proposal of adequate message retransmission schemes, in order to increase the reliability of message exchanges in industrial environments. To demonstrate the effectiveness of the proposed schemes, we present a simulation assessment of both the proposed message retransmission schemes and the Guaranteed Time Slots (GTS) mechanism, as defined by the standard. © 2012 IEEE.

关键词： Wireless sensor networks

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A LabVIEW-Based Simulator for the Activated Sludge Process

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IFAC Proceedings Volumes 2012年第2期45卷 942-947页

作者： Norhaliza Abdul Wahab Muhammad Sani Gaya Yahaya Md Sam Ulf Jeppsson Reza Katebi Control and Instrumentation Department Faculty of Electrical Engineering Universiti Teknologi MalaysiaUTM Skudai 81310 Johor Malaysia (Tel:+607-5535418) Div of Industrial Electrical Engineering and Automation (IEA) Dept of Measurement Technology and Industrial Electrical Engineering (MIE) Lund University Industrial Control Centre Dept of Electronic and Electrical Engineering University of Strathclyde Glasgow UK

Abstract The activated sludge process is the main process in most urban wastewater treatment systems. It is considered complex in nature, and building its mathematical model in practice becomes difficult. A simple and easy way to build the simulation models for the system is needed. In this paper, a LabVIEW based simulator for the system is presented. LabVIEW offers a highly efficient, simple and flexible platform for simulation and control. Building applications in LabVIEW require less coding, and debugging is easy and fast. The proposed simulator utilizes the Benchmark Simulation Model no.1 (BSM 1) for the biochemical reactor and clarification processes. The operation of the simulator is via a graphical user interface (GUI) built in the LabVIEW environment. The simulation results can be displayed in digital and graphical forms. Simulation results obtained were compared with the results from other software simulation packages in which the COST/IWA Simulation Benchmark has been implemented. The developed simulator is very useful due to its efficiency and accuracy in simulating the wastewater process model. The simulator can serve as a training tool for plant operators/students to provide them with better knowledge and understanding of the process.

关键词： Simulator LabVIEW Activated Sludge Process Wastewater Treatment Plant Simulation Benchmark

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Gradient method optimization of penicillin production

Gradient method optimization of penicillin production

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Chinese control and Decision Conference, CCDC

作者： Matej Pčolka Sergej Čelikovský Department of Control Engineering Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Information Theory and Automation AS CR Prague Czech Republic

关键词： Substrates Gradient methods Mathematical model Biomass Production Biological system modeling

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Personalized therapy selection by using multi-objective optimization

Personalized therapy selection by using multi-objective opti...

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IEEE International Conference on Intelligent engineering Systems (INES)

作者： Ivars Karpics Institute of computer control automation and computer engineering Faculty of computer science and information technology Riga Technical University Riga Latvia

In the article a therapy selection method by using topological modelling and multi- objective optimization is presented. In a medicine practice a doctor by taking into the count patients' health state and laboratory results, tries to suggest a treatment strategy, which mostly is a drug therapy. To solve this task a decision support system has been developed and proposed. The system includes a mathematical model of three self connected diseases. Therapies are evaluated by five efficiency objectives. To find the optimal therapy, seven multi- objective methods are selected and used. Optimization methods form decision support module which is implemented in the medical computer system. To evaluate a performance of the system, test examples are analysed. Conclusion includes the summary and proposals of further research.

关键词： Mathematical model Drugs Optimization methods Computers

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Development of fuzzy logic water bath temperature controller using MATLAB

Development of fuzzy logic water bath temperature controller...

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2012 IEEE International Conference on control System, Computing and engineering, ICCSCE 2012

作者： Hasim, Norhaslinda Aras, Mohd Shahrieel Mohd Rashid, Mohd Zamzuri Ab Kassim, Anuar Mohamed Abdullah, Shahrum Shah Department of Control and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Department of Mechatronics Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Department of Electric and Electronics Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia 54100 Kuala Lumpur Malaysia

ISBN: (纸本)9781467331432

In this paper, the development of a water bath temperature system to control the liquid's temperature in the water bath will be presented. In order to develop the water bath temperature control system, MATLAB fuzzy logic toolbox will be utilized. The Fuzzy Logic controller (FLC) is designed to control water temperature based on the input acquired from the thermal transducer sensor. The inference engines that are used are;Max-min (Mamdani) method and centre of gravity technique for defuzzification. The 4 × 4 matrix rules for the controller will be used in this project. In addition, the USB NI-DAQ card will be used as xPC target to link the MATLAB software and real time application. The real time output temperature is validated based on the simulation's temperature which is initially set by user. It can be concluded the performance of real time study is in par with the simulation result. © 2012 IEEE.

关键词： MATLAB

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A soft sensor development for the estimation of benzene content in catalytic reformate

A soft sensor development for the estimation of benzene cont...

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Proceedings of the International Convention MIPRO

作者： Željka Ujević Andrijić Romano Karlović Boris Žeželj Department of Measurement and Process Control Faculty of Chemical Engineering and Technology Zagreb Croatia Process Automation Rijeka Refinery Kostrena Croatia

As vehicle emission standards become more stringent, there is an increasing need for continual monitoring of benzene content in gasoline. Since the on-line analyzers are often unavailable, and laboratory analyses are infrequently obtained, soft sensors for the estimation of benzene content of light reformate are developed. Soft sensors are developed using system identification methods. Experimental data is acquired from the refinery distributed control system (DCS) and include continuously measured variables and analyzer assays available on-line. In the present work, the development of a Finite Impulse Response (FIR) model, an Output Error (OE) model and an Auto-Regressive Model with Exogenous Inputs (ARX) model are presented. To overcome the problem of selecting the best model parameters by trial and error, genetic algorithm was used. Based on developed soft sensors, it is possible to entirely replace on-line analyzers with soft sensors by embedding the model in a DCS on-site.

关键词： Mathematical model Finite impulse response filter Predictive models Autoregressive processes Data models Estimation Adaptation models

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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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Semantic Runtime Interface Description Based on engineering Knowledge

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IFAC Proceedings Volumes 2012年第6期45卷 805-810页

作者： Petr Novák Martin Melik-Merkumians Michael Steinegger Thomas Moser Radek Ŝindelář Alois Zoitl Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology AT-1040 Vienna Austria Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague 121 35 Prague Czech Republic Automation and Control Institute Vienna University of Technology AT-1040 Vienna Austria

Design and integration of industrial automation systems require cooperation of different engineering disciplines and various engineering tools during both design and run time. The scope of this paper is to bridge the gap between design-time description and runtime integration in a semi-automated way. Furthermore, we address the problem of integrating legacy systems with no access to original engineering data. It is assumed that an interface between a real industrial system and software automation tools is OPC Unified Architecture (UA) and we propose to derive the plant knowledge from the OPC UA tag list. Since it is not possible to solve this task in general, we require the tag list to adopt the naming convention of IEC 81346, which is widespread in large-scale systems. This tag list is parsed and the engineering knowledge is derived and stored in the engineering Knowledge Base. Consequently, the plant knowledge is mapped to knowledge related to software automation tools, such as simulators. The proposed methodology is evaluated on a real-life example dealing with a laboratory tank model.

关键词： automation Integration Knowledge-based systems Data acquisition OPC UA IEC 81346 Computer Simulation Software tools

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