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American control Conference (ACC)

作者： W.A. Docter C. Georgakis Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem PA USA

Presents a general methodology for the identification of average linear low order models (ALLOM) from data collected from detailed nonlinear models. While there are many methods available in the literature for identifying linear models, these methods tend to produce inaccurate and ill-conditioned models when used on nonlinear data sets. The method in this paper differs from traditional linearization methods in that it better approximates the dynamic characteristics over a wider area around the reference steady state.

关键词： Signal processing Predictive models Open loop systems chemical processes process control chemical engineering Steady-state Separation processes Thermodynamics State estimation

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Closed-Loop Identification of State Space Models using Subspace Techniques

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IFAC Proceedings Volumes 1997年第9期30卷 37-42页

作者： Hemant Jha Christos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania 18015 Phone: (610)-758-5432 Fax:(610)-758-5297

The paper presents a subspace algorithm which identifies the process model from closed-loop data. The algorithm is based on the use of a closed-loop oblique projection for the direct identification of the plant dynamics. This closed-loop oblique projection is particularly useful because it eliminates the use of a minimal realization step after the identification has been performed. Similar to the open-loop algorithm, the proposed closed-loop algorithm is ideally suited for MIMO problems.

关键词： Closed-loop Identification Subspace Methods State Space Models Multivariable Systems Matrix Projection

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Real-time estimation and control of particle size in semi-batch emulsion polymerization

Real-time estimation and control of particle size in semi-ba...

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American control Conference (ACC)

作者： V. Liotta C. Georgakis M.S. El-Aasser Air Products and Chemicals Inc. Allentown PA USA Chemical Process Modeling and Control Research Center and Emulsion Polymers Institute Lehigh University Bethlehem PA USA

The control of the relative particle growth of a bidisperse emulsion polymerization is investigated in an automated reactor control facility capable of online density and online particle size measurements. Final diameter ratio values are controlled by manipulating the monomer feed rate to the reactor using a control scheme comprised of a parameter adaptive Kalman filter with steady state gains and a nonlinear model predictive controller. One of the main features of the implemented controller is the connection of the prediction horizon to the criterion that the overall conversion equal 90% at the end of the batch. Feedback is incorporated into the algorithm at each sampling time by starting the model prediction calculation at the current estimated values of the model states. The controller performs well to meet a challenging diameter ratio set point at the end of the batch. The robustness of the controller to reject an induced initial initiator concentration disturbance is demonstrated.

关键词： Size control Automatic control Predictive models Inductors Polymers Size measurement Feeds Programmable control Adaptive control Steady-state

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Reference system based model predictive control

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IFAC Proceedings Volumes 1996年第1期29卷 5923-5928页

作者： Lokesh Kalra Chriatos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA

Despite recent advances in the field, the tuning of presently popular Model Predictive control formulations is largely a trial and error procedure. Motivated by this fact, a Reference System based tuning is explored through Reference System Model Predictive control. The RS-MPC algorithm is examined because of its potentially more intuitive approach to tuning. Under this methodology the tuning involves the selection of two parameters for each controlled variable. The first parameter adjusts the shape of the response and the second one affects the speed. Using these, instead of the weight-based tuning of conventional MPC, much of the trial and error is eliminated. The most important features of the controller arc elucidated through the performance of the STSO and MIMO cases for the Amoco Fluid Catalytic Cracker process simulation.

关键词： Multivariable Feedback control Predictive control Models Tuning Characteristics control Algorithms Simulators

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Decentralized PCA Charts for Performance Assessment of Plant-Wide control Structures

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IFAC Proceedings Volumes 1996年第1期29卷 5894-5898页

作者： Christos Georgakis Bethany Steadman Vincenzo Liotta Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA

Static principal component analysis (PCA) statistical charts are used to assess and compare the performance of two plant-wide control strategies of the Tennessee Eastman process. Both centralized and decentralized charts are used as well as charts relating to the energy and material balance of the process. In most cases these charts reveal the origin of the disturbance and the effectiveness of the control structure to compensate for the disturbance. Differences and similarities between the two control structures are also examined.

关键词： process control large scale systems multivariable feedback systems multivariable quality control control schemes disturbance localization disturbance rejection

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Evaluation of subsurface oxygen sensors for remediation monitoring

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GROUND WATER MONITORING AND REMEDIATION 1996年第1期16卷 106-111页

作者： Li, DX Lundegard, PD Dong X. Li (Unocal Environmental Technology Group 376 S. Valencia Ave. Brea CA 92621) is a research engineer and has been a member of Unocal's Environmental Technology Group since 1991. Currently he is involved in several bioventing field studies using innovative sensor technology. He has worked on vapor biofiltration and soil bioventing for petroleum hydrocarbon removal in the past two years. He also worked on air emission control issues including hydrogen sulfide abatement in the refinery processes and pilot plant study on Unocal's Selectox process. Dong received a B.S. from Cal Poly University Pomona and an M.S. and a Ph.D. from Washington State University all in chemical engineering. Paul D. Lundegard (Unocal Environmental Technology Group 376 S. Valencia Ave. Brea CA 92621) received a B.S. in geology from the College of William and Mary an M.S. in geology from the University of Cincinnati and a Ph.D. in geology from the University of Texas at Austin. He is a California registered geologist and has worked at the Unocal Fred L. Hartley Research Center since 1985. His research on air sparing behavior involves high-level field investigations coupled with numerical simulation.

Continuous remediation monitoring using sensors is potentially a more effective and inexpensive alternative to current methods of sample collection and analysis. Gaseous components of a system are the most mobile and easiest to monitor. Continuous monitoring of soil gases such as oxygen, carbon dioxide, and contaminant vapors can provide important quantitative information regarding the progress of bioremediation efforts and the area of influence of air sparging or soil venting. Laboratory and field tests of a commercially available oxygen sensor show that the subsurface oxygen sensor provides rapid and accurate data on vapor phase oxygen concentrations. The sensor is well suited for monitoring gas flow and oxygen consumption in the vadose zone during air sparging and bioventing. The sensor performs well in permeable, unsaturated soil environments and recovers completely after being submerged during temporary saturated conditions. Calibrations of the in situ oxygen sensors were found to be stable after one year of continuous subsurface operation. However, application of the sensor in saturated soil conditions is limited. The three major advantages of this sensor for in situ monitoring are as follows: (1) it allows data acquisition at any specified time interval;(2) it provides potentially more accurate data by minimizing disturbance of subsurface conditions;and (3) it minimizes the cost of field and laboratory procedures involved in sample retrieval and analysis.

关键词： Oxygen sensors

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A device simulation of the BBT effect in flash memory cells and implications for the development of high-reliability memory cells

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ELECTRONICS AND COMMUNICATIONS IN JAPAN PART II-ELECTRONICS 1996年第11期79卷 51-57页

作者： Hayashi, T Fukuda, K Ohno, M Nishi, K Kita, A VLSI R&D Center OKI Electric Industry Company Ltd. Hachioji-shi Japan 193 Graduated from the Science University of Tokyo Dept. of Applied Physics in 1986 and joined Oki Electric. Since then he has been engaged in research on the reliability of MOS transistors and silicon oxide films. Since 1994 he has been engaged in the development of flash memory. He is a member of the Applied Physics Society. Graduated from the University of Tokyo Dept. of Applied Physics in 1983 and joined Oki Electric in 1985. Since then he has been engaged in research on the semiconductor process and device simulation. In 1990 he participated in joint research at the Technical University of Aachen. He is a member of the Applied Physics Society. Graduated from the Tokyo University of Agriculture and Technology Dept. of Electrical Engineering in 1980 and completed an MS course in 1983. In 1986 he completed the doctoral course at Shizuoka University. He then joined Oki Electric where he has been engaged in research on ULSI processes. He is now a manager responsible for flash memory at the VLSI R&D Center. He holds a doctorate in engineering. He is a member of the Applied Physics Society. Graduated from the University of Tokyo Dept. of Applied Physics in 1973 and joined Oki Electric. He was engaged in the development of integrated circuit logic simulation technology and bipolar process technology and since 1980 he has been engaged in research on process/device simulation and modeling. Presently he is a senior manager at the VLSI R&D Center. In 1982–1984 he was a Visiting Scholar at MIT. He holds a doctorate in engineering. He is a member of the Applied Physics Society and a senior member of IEEE. Graduated from Tokyo Institute of Technology Dept. of Chemical Engineering in 1978 and completed the MS program in 1930. In that year he joined Oki Electric. Since then he has been engaged in CMOS process design for DRAM and flash memory. He is now a manager at the VLSI R&D Center. He is a member of the Applied Physics Society.

In order to analyze the BBT (band-to-band tunneling) phenomenon in flash memory cells by simulation, a new model is proposed, which improves on the BBT model by introducing the concept of ''average electric field.'' This model agrees well with the measured results in a wide drain N-concentration range. Using this model, the reliability of memory cells is analyzed. It is found that the difference of the amount of BBT generation does not directly affect the endurance characteristics but does affect the disturb characteristics. The same model can be used to analyze problem points of the present cells and to estimate the BBT current of next-generation devices accurately.

关键词： band-to-band tunneling flash memory simulation endurance characteristics

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Wavelet techniques in the compression of process data

Wavelet techniques in the compression of process data

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American control Conference (ACC)

作者： M.J. Watson A. Liakopoulos D. Brzakovic C. Georgakis Chemical Process Modeling and Control Research Center Lehigh University USA Chemical Process Modeling and Control Research Center Lehigh University Bethlehem PA USA

The objective of this paper is to explore the application of wavelets to the field of data compression in the process industry. The wavelet transform is compared with the discrete Fourier and cosine transforms. To examine a complete approach to data compression, quantization techniques are applied to the transformed coefficients. Different quantiser designs are used for the compression of data from an industrial distillation column. Comparisons are made with the Box-Car and backward-slope methods currently used in the process industries.

关键词： Data compression Discrete wavelet transforms Quantization chemical processes process control chemical industry Industrial control Discrete Fourier transforms Fourier transforms Frequency

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Abstracts of papers presented at the 14th conference of the Weed Science Society of Israel Abstracts of papers presented at the international conference on controlled atmosphere and fumigation (CAF) in stored products Abstracts of papers presented at the joint international conference of FAOPMA — CEPA on pest control in the 21st century Abstracts of papers presented at the 2nd international Agro-Ecology Symposium on integrated pest management: from the drawing board to the market

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Phytoparasitica 1996年第3期24卷 199-265页

作者： E. Yogev M. Berson Y. Benyamini Y. Sheinboim T. Lev-Ran A. Bahat Y. Barkai Y. Gatti M. Zaidan O. Barazani Y. Boshvize S. Graph U. Luchinsky T. Blumenfeld Y. Kleifeld G. Herzlinger H. Bucsbaum S. Golan T. Chilf R. Aly Y. Ohali A. Ovadia Y. Chachlon H. Yovel Y. Tesler G. Colodney A. Nir S. Zarka A. Tal B. Rubin T. Yaacoby Y. Alon Y. Kedar Orit Ben-Zvi Assaraf O. Shainberg H. D. Rabinowitch E. Tel-Or Y. Goldwasser D. M. Joel D. Plakhine V. Portnoy G. Tzuri N. Katzir Dalia Losner-Goshen A. M. Mayer R. Jacobsohn Z. Tanaami H. Eisenberg Ziva Amsellem Z. Kernyi L. Hornok J. Gressel Adiva Shomer-Ilan Ela Nir Daphna Michaeli V. Kampel A. Warshawsky M. Yogev M. Negbi J. Hershenhorn Y. Lavan T. Hilf M. Horowitz M. Cohen I. Hirsch A. Veneziani S. T. Conyers C. H. Bell Ana C. Sá-Fischer C. S. Adler Ch. Reichmuth P. W. Flinn D. W. Hagstrum G. N. Mbata R. G. Winks Elisabeth A. Hyne M. Q. Chaudhry A. D. MacNicoll N. R. Price M. Schöller J. -F. Dugast R. Plarre S. Navarro E. J. Donahaye R. Diaz Miriam Rindner A. Azrieli P. Trematerra F. Fontana M. Mancini Ailsa D. Hocking Marta H. Taniwaki J. Lacey A. Hamer N. Magan N. Paster F. M. Caliboso D. G. Alvindia G. C. Sabio M. T. dela Cruz Okky Setyawati Dharmaputra A. S. R. Putri M. Sidik Eleni Papademetriou A. Varnava C. Mouskos M. A. Malek B. Parveen K. A. Dzisi W. O. Ellis Ana Maria Estevez Ljubica Galletti T. Fichet E. Oteiza L. A. Lizana M. X. Gonzalez B. Yakobson Y. Slavezky H. Ephrati El-H. Bartaly R. K. Kashyap M. Gupta W. L. Kashyap B. S. Dahiya A. K. Dash J. R. Rangaswamy R. D. Shroff D. S. Jayas W. E. Muir N. D. G. White L Gaye Weller J. E. van S. Graver Wu-Kang Peng M. Bengston E. Alip C. Reed J. G. Leesch G. F. Knapp G. F. Russell L. B. Llewellin Ch. Ulrichs H. J. Banks P. C. Annis R. Allanson R. Tauscher K. Westphal S. Mohan M. Gopalan P. C. Sumdarababu V. V. Sree Narayanan Sabine Prozell G. Ziegleder B. Schartmann R. Matissek J. Kraus D. Gerard S. Rogg W. Raemann R. F. Ryan Ya-Nan Wang R. T. Noyes P. Kenkel J. T. Criswell G. W. Cuperus C. J. Waterford C. P. Whittle L. Be Luxembourg Chemicals and Agriculture Ltd. Tel Aviv Israel Agrochemicals Dept. Milchan Bros. Ltd. Ramat Gan Israel Extension Service Ministry of Agriculture Zefat Mevo Hamma Ramat HaGolan Israel Dept. of Weed Science ARO Newe Ya’ar Research Center Haifa Israel Agrochemicals Department Milchan Bros. Ltd. Ramat Gan Israel Tarsis-Agrichem Tel Aviv Israel Weed Control Co. Ltd. Bet Dagan Israel Dept. of Field Crops Vegetables and Genetics The Hebrew University of Jerusalem Faculty of Agriculture Rehovot Israel Plant Protection and Inspection Services Ministry of Agriculture Bet Dagan 50250 Agan Chemical Manufacturers Ltd. Ashdod Israel Dept. of Field Crops Vegetables and Genetics Rehovot Dept. of Agricultural Botany The Hebrew University of Jerusalem Faculty of Agriculture Rehovot Israel Dept. of Weed Science ARO Newe Ya’ar Research Center Haifa Dept. of Botany The Hebrew University of Jerusalem Jerusalem Israel Dept. of Vegetable Crops ARO The Volcani Center Bet Dagan Israel Dept. of Plant Genetics Weizmann Institute of Science Rehovot Israel Inst. for Plant Science Agricultural Biotechnology Center Gödöllö Hungary Dept. of Botany Tel-Aviv University Tel Aviv Israel Dept. of Plant Genetics The Weizmann Institute of Science Rehovot Israel Dept. of Organic Chemistry The Weizmann Institute of Science Rehovot Israel Dept. of Ornamental Horticulture ARO The Volcani Center Bet Dagan Israel Weed Control Co. Ltd. Bet Dagan Chem-Nir Ltd. Kefar Shemaryahu Tiveon-Chem Co. Haifa Israel Central Science Laboratory Ministry of Agriculture Fisheries and Food Slough Berks UK Federal Biological Research Centre for Agriculture and Forestry Inst. for Stored Product Protection Berlin Germany USDA-ARS Grain Marketing and Production Research Center Manhattan USA School of Biological Sciences Abia State University Uturu Nigeria CSIRO Division of Entomology SCMC Nambour CSIRO Division of Entomology Canberra Australia DowElanco Europe Letcombe Laboratory L

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Disturbance detection and isolation by dynamic principal component analysis

Disturbance detection and isolation by dynamic principal com...

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作者： Ku, Wenfu Storer, Robert H. Georgakis, Christos Chemical Process Modeling and Control Research Center Iacocca Hall Lehigh University 111 Research Dr. Bethlehem PA 18015 United States Department of Chemical Engineering Department of Industrial Engineering

In this paper we extend previous work by ourselves and other researchers in the use of principal component analysis (PCA) for statistical process control in chemical processes. PCA has been used by several authors to develop techniques to monitor chemical processes and detect the presence of disturbances [1-5]. In past work, we have developed methods which not only detect disturbances, but isolate the sources of the disturbances [4]. The approach was based on static PCA models, T2 and Q charts [6], and a model bank of possible disturbances. In this paper we use a well-known 'time lag shift' method to include dynamic behavior in the PCA model. The proposed dynamic PCA model development procedure is desirable due to its simplicity of construction, and is not meant to replace the many well-known and more elegant procedures used in model identification. While dynamic linear model identification, and time lag shift are well known methods in model building, this is the first application we are aware of in the area of statistical process monitoring. Extensive testing on the Tennessee Eastman process simulation [7] demonstrates the effectiveness of the proposed methodology.

关键词： Principal component analysis

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