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IEEE International Conference on Automation and Logistics

作者： Dabo Xu Jie Huang Applied Control and Computing Laboratory Department of Mechanical and Automation Engineering Chinese University of Hong Kong New Territories Hong Kong China

This paper develops an approach to dealing with the global robust output regulation problem for a class of nonlinear systems with integral input-to-state stable (iISS) inverse dynamics by using output feedback control. As iISS condition is strictly weaker than ISS condition, the result of this paper applies to a larger class of nonlinear systems.

关键词： Robustness Trajectory Mathematical model Output feedback Equations Radio frequency Nonlinear systems

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A New On-Line Indicator of Biopolymer Content in Bacterial Cultures

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IFAC Proceedings Volumes 2010年第6期43卷 192-196页

作者： P. Hrnĉiřík J. Vovsík J. Náhlík Department of Computing and Control Engineering Institute of Chemical Technology Prague Technická 5 166 28 Praha 6 Czech Republic (Tel: +420 220 444 174

This paper describes the application of an impedance spectroscopy based analyser in combination with standard off-gas measurements for on-line monitoring of an intracellular biopolymer accumulation during a bioproduction process (Pseudomonas putida KT2442 fed-batch cultivation). Using exclusively on-line measurements a new physiological indicator of biopolymer accumulation in bacterial cells is proposed. The indicator, which could be referred to as an “obesity” quotient, is based on capacitance difference signal carrying information on number of cells and cumulative oxygen consumption related to dry cell weight.

关键词： Fermentation processes Capacitance Monitoring Biopolymer production

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Observer-based sliding mode control for a class of discrete systems via delta operator approach

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Journal of the Franklin Institute 2010年第7期347卷 1199-1213页

作者： Hongjiu Yang Yuanqing Xia Peng Shi Department of Automatic Control Beijing Institute of Technology Beijing 100081 China Department of Computing and Mathematical Sciences University of Glamorgan UK School of Engineering and Science Victoria University Melbourne VIC8001 Australia

In this paper, an observer-based sliding mode control (SMC) problem is investigated for a class of uncertain delta operator systems with nonlinear exogenous disturbance . A novel robust stability condition is obtained for a sliding mode dynamics by using Lyapunov theory in delta domain. Based on a designed sliding mode observer, a sliding mode controller is synthesized by employing SMC theory combined with reaching law technique. The robust asymptotical stability problem is also discussed for the closed-loop system composed of the observer dynamics and the state estimation error dynamics . Furthermore, the reachability of sliding surfaces is also investigated in state-estimate space and estimation error space, respectively. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the developed method.

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A novel approach to the model reference adaptive control of MIMO systems

A novel approach to the model reference adaptive control of ...

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19th International Workshop on Robotics in Alpe-Adria-Danube Region, RAAD 2010

作者： Tar, J.K. Rudas, I.J. Bitó, J.F. Kozlowski, K.R. Pozna, C. Institute of Intelligent Engineering Systems John von Neumann Faculty of Informatics Ó Buda University Bécsi út 96/B H-1034 Budapest Hungary Department of Control and Systems Engineering Computing Science and Management Poznań University of Technology Piotrowo 3a 60-965 Poznań Poland Design and Robotics Department University Transilvania of Brasov Bd. Eroilor 29 Brasov Romania

ISBN: (纸本)9781424468867

The "Model Reference Adaptive control (MRAC)" is a popular approach from the early nineties to our days. Its basic idea is the application of proper feedback that makes the behavior of the controlled system identical to that of the "reference model" that normally is simple enough to control. The idea has many particular variants with the common feature that they are designed by the use of Lyapunov's 2nd ("direct") method that normally applies a quadratic Lyapunov function constructed of the tracking error and further additional terms. Though this approach normally guarantees global asymptotic stability, its use can entail complicated tuning that may have disadvantages whenever very fast applications are needed. In this paper an alternative problem tackling, the application of "Robust Fixed Point Transformations (RFPT)" in the MRAC technique is recommended. This approach applies strongly saturated, multiplicative nonlinear terms causing a kind of "deformation" of the input of the available imprecise system model. Instead parameter tuning that is typical in the traditional MRAC it operates with a simple convergence guaranteed only within a local basin of attraction. This technique can well compensate the simultaneous consequences of modeling errors and external disturbances that normally can "fob" the more traditional, tuning based approaches. As a potential application paradigm the novel MRAC control of a "cart-beam-hamper" system is considered. The conclusions of the paper are illustrated by simulation results. © 2010 IEEE.

关键词： Model reference adaptive control

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A Framework for Nonlinear Output Regulation for Time-varying Uncertain Systems

A Framework for Nonlinear Output Regulation for Time-varying...

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2010 49th IEEE Conference on Decision and control

作者： Xi Yang Jie Huang Applied Control and Computing Laboratory Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin N.T. Hong Kong

ISBN: (纸本)9781424477456

Recently, the global robust output regulation problem for nonlinear time-varying systems is considered in [14] under the assumption that the exosystem is exactly known. This paper further considers the case where the time-varying exosystem is unknown. Conditions are given under which the problem can be converted into an adaptive stabilization problem of an augmented time-varying nonlinear system. The problem is solved for a class of time-varying output feedback systems with a time-varying uncertain exosystem.

关键词： Nonlinear output regulation Time-varying systems Adaptive control

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The Determination of Microbicidal Effects of Corona Discharge Using the Image Analysis

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IFAC Proceedings Volumes 2010年第24期43卷 227-231页

作者： H. Sousková L. Kommová V. Scholtz A. Korbářová J. Julák Department of Computing and Control Engineering Institute of Chemical Technology in Prague Czech Republic Department of Physics and Measurement Institute of Chemical Technology in Prague Czech Republic First Faculty of Medicine Charles University in Prague Czech Republic

This paper presents an experimental apparatus for the decontamination and sterilization of water suspension of microorganisms and demonstrates the application of image analysis for the evaluation of decontamination efficiency by automatic counting of colonies on surface of cultivating medium. It was shown that the presented procedure of image analysis is adequate for this problem. The error of the automated cfu counting procedure is less than 5% in the comparison with manual counting. From the microbiological point of view it was found, that total inhibition of all four bacterial species and one of yeast occurs after 3 and 6 minutes of exposition to the corona discharge. Total inhibition of mould spores occurs after 20 minutes for one of used species only but it does not occurs even after 30 minutes of exposition for next two species under study.

关键词： Corona discharges image analysis sterilization microorganisms biotechnology

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Multi-Channel EEG Signal Segmentation and Feature Extraction

Multi-Channel EEG Signal Segmentation and Feature Extraction

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International Conference on Intelligence engineering Systems

作者： Ales Prochazka Martina Mudrova Oldfich Vysata Robert Hava Carmen Paz Suarez Araujo Institute of Chemical Technology in Prague Department of Computing and Control Engineering Neurocenter Caregroup Czech Republic Universidad de Las Palmas de G.C.

ISBN: (纸本)9781424476527

Signal analysis of multi-channel data form a specific area of general digital signal processing methods. The paper is devoted to application of these methods for electroencephalogram (EEG) signal processing including signal de-noising, evaluation of its principal components and segmentation based upon feature detection both by the discrete wavelet transform (DWT) and discrete Fourier transform (DFT). The self-organizing neural networks are then used for pattern vectors classification using a specific statistical criterion proposed to evaluate distances of individual feature vector values from corresponding cluster centers. Results achieved are compared for different data sets and selected mathematical methods to detect and to classify signal segments features. Proposed methods are accompanied by the appropriate graphical user interface (GUI) designed in the MATLAB environment.

关键词： Electroencephalography Feature extraction Discrete wavelet transforms Discrete Fourier transforms Graphical user interfaces Signal analysis Digital signal processing Signal processing Signal denoising Computer vision

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Feature selection for semi-supervised multi-label learning with application to gene function analysis 10

Feature selection for semi-supervised multi-label learning w...

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Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology

作者： Li, Guo-Zheng You, Mingyu Ge, Lei Yang, Jack Y. Yang, Mary Qu MOE Key Laboratory of Embedded System and Service Computing Tongji University Shanghai 201804 China Department of Control Science and Engineering Tongji University Shanghai 201804 China School of Computer Science and Engineering Shanghai University Shanghai 200072 China Purdue Univ. ECE West Lafayette IN 47907 United States Indiana Univ. Bioinformatics Center Indianapolis IN 46202 United States

ISBN: (纸本)9781450304382

This paper investigates gene function annotation of Yeast by using semi-supervised multi-label learning. Multi-label learning has been a hot topic in the bioinformatics field, but there are many samples unlabeled. Semi-supervised learning may be employed to utilize the unlabeled data. This paper proposes a novel semi-supervised multi-label learning algorithm COMN by combining Co-Training with ML-kNN to utilize the unlabeled yeast gene data to improve modeling accuracy of function annotation. Furthermore, an embedded feature selection algorithm PRECOMN is proposed to perform feature selection for COMN to remove the irrelevant and redundant features. Experimental results on one benchmark data set of Yeast show COMN and PRECOMN perform better than the original multi-label learning algorithm ML-kNN. Furthermore PRECOMN improves generalization performance of COMN. Copyright © 2010 ACM.

关键词： Feature Selection

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Solving NP-complete problems by spiking neural P systems with budding rules

Solving NP-complete problems by spiking neural P systems wit...

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10th International Workshop on Membrane computing, WMC 2009

作者： Ishdorj, Tseren-Onolt Leporati, Alberto Pan, Linqiang Wang, Jun Computational Biomodelling Laboratory Åbo Akademi University Department of Information Technologies 20520 Turku Finland Università degli Studi di Milano - Bicocca Dipartimento di Informatica Sistemistica e Comunicazione Viale Sarca 336/14 20126 Milano Italy Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Research Group on Natural Computing Department of CS and AI University of Sevilla Avda Reina Mercedes s/n 41012 Sevilla Spain

ISBN: (纸本)3642114660

Inspired by the growth of dendritic trees in biological neurons, we introduce spiking neural P systems with budding rules. By applying these rules in a maximally parallel way, a spiking neural P system can exponentially increase the size of its synapse graph in a polynomial number of computation steps. Such a possibility can be exploited to efficiently solve computationally difficult problems in deterministic polynomial time, as it is shown in this paper for the NP-complete decision problem sat. © 2010 Springer-Verlag.

关键词： Computational complexity

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Continuous Noninvasive Blood Pressure Measurement by Near Infra Red CCD Camera and Pulse Transmit Time Systems

Continuous Noninvasive Blood Pressure Measurement by Near In...

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International Conference on Computer engineering and Applications (ICCEA)

作者： Petr Zurek Ondrej Krejcar Marek Penhaker Martin Cerny Robert Frischer Department of Measurement and Control Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Automation and Computing in Metallurgy Faculty of Metallurgy and Materials Engineering Technical University of Ostrava Ostrava Czech Republic

ISBN: (纸本)9781424460793;9780769539829

The need of continuous blood pressure measurement is usable in wide spectrum of applications from physicians practice to home care applications. Many types of blood pressure measurement devices can be bought in electronics shops. All such devices are contact measurement devices which need to be in contact of human body (hand or foot mainly). Secondary they allow only one measurement per several minutes interval (typically ones in 10 minutes). Our goal is to develop a small device for noninvasive continuous measurement of blood pressure. This device must be a small battery powered embedded system which measure a blood pressure during a long time period and send this information remotely to operator's stations. We would like to try two systems of blood pressure monitoring. The first one is system with NIR CCD camera (Near Infra Red), which measure the wide changes of the blood vessels and the second one is system, which measure the pulse transmit time (PTT). At the end we can compare the systems and get information, which system will be a right way to obtain exact continuous blood pressure information.

关键词： Pulse measurements Blood pressure Pressure measurement Time measurement Charge coupled devices Charge-coupled image sensors Biomedical monitoring Battery charge measurement Humans Foot

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