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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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MULTIVARIABLE NONLINEAR AND ADAPTIVE-control OF A DISTILLATION COLUMN

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AICHE JOURNAL 1995年第1期41卷 195-199页

作者： STROMBORG, KB TOIVONEN, HT HAGGBLOM, KE WALLER, KV Process Control Lab. Dept. of Chemical Engineering Åbo Akademi University 20500 Åbo Finland

Multivariable nonlinear and adaptive control was applied to a binary distillation column. Experimental process information in terms of linear process models valid at different operating points was used to obtain a bilinear process model. Because experimental process information is often in practice available as linear models at different operating points, the modeling procedure is likely to be useful for process control in general. The process was controlled by a discrete-time multiinput/multioutput PID controller, whose model-dependent parameters were calculated at each sampling instant from a linearized form of the bilinear model. In this way, uniform performance was obtained over the whole operating range of interest. A similar controller with fixed parameters did not perform satisfactorily in this respect. Because the bilinear model is linear in the parameters, these could also be estimated on-line by standard parameter estimation methods. The resulting adaptive controller, based on the same design procedure as the previous controller, also performed satisfactorily over the whole operating range.

关键词： Distillation columns

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Studies in plant-wide controllability using the Tennessee Eastman Challenge problem, the case for multivariable control

Studies in plant-wide controllability using the Tennessee Ea...

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American control Conference (ACC)

作者： D.R. Vinson C. Georgakis J. Fossy Air Products and Chemicals Inc. Allentown PA USA Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem PA USA

The design and application of a new control structure for the Tennessee Eastman Challenge process is presented. This structure is primarily single-input single-output (SISO) but it has been augmented with the concept of extensive variable control to intuitively design multivariable structures for the regulation of the production rate and the product purities. A review of plant-wide control methodologies is provided to lay the basis for a discussion of SISO versus multivariable approaches.

关键词： controllability Computer aided software engineering control systems process design chemical products chemical processes process control Steady-state Recycling Production systems

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Bilinear Identification of Nonlinear processes

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IFAC Proceedings Volumes 1994年第2期27卷 47-52页

作者： James F. Bartee Christos Georgakis Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA 18015 Fax: (610)758-5432 Internet

Identification of nonlinear processes using bilinear models is presented. To avoid direct estimation of the bilinear model parameters, a dynamically equivalent input/output model structure is developed through an analysis of the observability of the bilinear system. Calculation of the Volterra kernels from the input/output model parameters is presented and the overparameterization of the input/output model form is examined by comparison with the Volterra series model form. Constraint equations calculated from this guarantees the dynamic equivalence of the input/output and state-space forms. The input/output model parameters are estimated through an extended least-squares method. An example of a fluid catalytic cracking unit (FCCU) is presented.

关键词： Nonlinear Identification Bilinear Models Input/Output Models Volterra Kernels FCCU

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A Method for Assessing the Effects of Design Parameters on controllability

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IFAC Proceedings Volumes 1994年第7期27卷 85-91页

作者： P.R. Lyman W.L. Luyben Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA 18015 Phone:(610)758-4256 Fax:(610)758-5297

A method is presented for identifying process design modifications that improve process controllability. The methodology includes the use of designed experimentation to examine multiple design and control factors simultaneously. Each trial within the designed experiment includes estimation of the capital and operating costs and quantification of the controllability. A recycle process is used in an example of the method. The method reveals that the size of the reactor has a large influence on the controllability and the control structures in combination with the other factori show potential for dynamic response improvement. Physical arguments are used to explain these observations.

关键词： Computer simulation control system analysis control system design dynamic response simulation sensitivity analysis

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The Effects of Operational and Design Characteristics of Catalytic Cracking Reactors on the Closed-Loop Performance of Linear Model Predictive controllers

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IFAC Proceedings Volumes 1994年第7期27卷 209-214页

作者： Lokesh Kalra Christos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania 18015 USA Phone:(610)758-543t Fax:(610)758-5t97

In closed-loop simulations of the catalytic cracker, it was observed that the model identified at a low throughput operating point, when used in MPC did a better job on the high throughput operating point than a model identified at the latter operating point. At the same time MPC utilising a model identified at a high throughput operating point did not perform well when used at the low throughput operating points. In this paper we examine this behavior through an analysis of the closed-loop catalytic cracker under unconstrained MPC. The persistent appearance of an upward spike in stack carbon monoxide concentrations immediately following a disturbance, despite extensive tuning efforts suggests that it is due to process rather than control system design characteristics. At high throughput operating points this phenomenon is of concern because it seriously impairs the ability of a control system to keep CO below its upper constraint. In the paper we trace the source of this dynamic behavior to the design of the catalytic cracker and suggest modifications that may favorably affect control performance.

关键词： Catalytic Cracking Model Predictive control Nonlinear control

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Model-based verification of batch process control software

Model-based verification of batch process control software

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IEEE International Conference on Systems, Man and Cybernetics

作者： S. Kowalewski R. Gesthuisen V. Rossmann Process Control Group Chemical Engineering Department University of Dortmund Dortmund Germany Technische Universitat Dortmund Dortmund Nordrhein-Westfalen DE Dept. of Chem. Eng. Dortmund Univ. Germany

The paper describes an approach to verify control software for batch processes. We look at logic controller programs specified as sequential function charts (SFCs). The basis of the verification is a Boolean condition/event (BC/E) model of the uncontrolled behavior of the batch plant. The control program to verify is translated into a BC/E system representation and then connected to the plant model. The verification process consists of a comparison of the set of reachable states of the resulting system and a set of forbidden states. The approach is applied to an existing lab plant.< >

关键词： process control Logic Software safety chemical engineering Humans Software testing Software performance Performance evaluation Application software Uncertainty

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MPSA abstracts

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Journal of Protein Chemistry 1994年第5期13卷 515-543页

作者： Aminlari, Mahmoud Asquith, Thomas Sarlo, Katherine Bailey, Jerome M. Tu, Oanh Issai, Gilbert Ha, Alice Shively, John E. Bell, Alexander W. Baur, Nicole C. Bergeron, John J. M. Ou, Wei -Jia Thomas, David Y. Cianflone, Katherine Baldo, Allain Hincke, Maxwell T. Momparler, Richard L. Laliberté, Josée Thomson, David M. P. Sutherland, M. Besada, Vladimir Gonzalez, Javier Padron, Gabriel Garay, Hilda Reyes, Osvaldo Takao, Toshifumi Shimonishi, Yasutsugu Bischoff, Rainer Roecklin, Dominique Bouchon, Bernadette Klarskov, Klaus Van Dorsselaer, Alain Brake, Patricia G. Pacitti, Anne Higgins, Terry Stevis, Panos Malinowski, John McElhiney, Sue Huang, Janes Vestal, Christine Buckel, Scott D. Stevenson, Tracy Loo, Joseph A. Caffrey, Martin Wang, Jin Wallace, Carmichael J. A. Clark-Lewis, Ian Carraway, C. A. Carothers Huang, J. Li, Y. Juang, S. -H. Gallo, A. Mayer, B. J. Carraway, K. L. Coleman, Patrick L. Sarpong, Daniel Deerfield, David W. Holland-Minkley, Amanda Hempel, John D. Nicholas, Hugh B. Denslow, Nancy D. Folmar, Leroy C. Sullivan, Craig V. Dixon, James D. Mark, Jonathan P. Elicone, Christopher P. Maleknia, Simin D. McGuinness, Brian F. Regnier, Fred E. Afeyan, Noubar B. Dolence, Julia M. Poulter, C. Dale Egorov, Tsezi Musolyamov, Alexander Popineau, Yves Andersen, Jens Roepstorff, Peter Falkenstein, Roberto J. Biscoglio de Jiménez Bonino, Mirtha J. Peña, Clara Gauggel, D. L. Asquith, T. N. Isfort, R. J. Miller, N. S. Cody, D. B. Giblin, Michael F. Wong, Tuck C. Quinn, Thomas P. Grant, Gregory A. Crankshaw, Mark W. Griffith, Scott Schroeder, Steve Quinn, Thomas Guinet, F. Petillot, Y. Chapsal, J. M. Dubayle, J. Greco, F. Barge, O. Forest, E. Valentin, C. Hahn, Frederick M Baker, Jonathan A. Haniu, Mitsuru Kenney, William C. Rohde, Michael F. Harman, James G. Lee, Eun Ju Glasgow, Joel Lew, Sew Fen Belduz, Ali O. Harris, Reed J. Molony, Michael S. Keyt, Lene H. Wu, Shiaw -Lin Hawke, David H. Tso, Jaqueline Early, Sherrell Miller, Chad G. Hayman, G. Thomas Miernyk, Jan A. Hellman, Ulf Wernstedt, Christer Góñez, Jorge H Department of Biochemistry School of Veterinary Medicine Shiraz University Shiraz Iran Corporate Professional & Regulatory Services/Human Safety Dept. The Procter & Gamble Co. Cincinnati Division of Immunology Beckman Research Institute of the City of Hope Duarte Protein Analytic Facility Sheldon Biotechnology Centre USA McGill University Montreal Department of Anatomy USA Biotechnology Research Institute NRC Canada Division of Cardiology Royal Victoria Hospital USA Department of Anatomy University of Ottawa Faculty of Health Science Ottawa Centre de Recherche Pediatrique Hôpital Ste-Justine Université de Montréal Montreal Department of Immunology Montreal General Hospital USA Center for Genetic Engineering & Biotechnology Cuba Institute for Protein Research Osaka University Osaka Japan Protein Analytical Group TRANSGENE S.A. Strasbourg Cedex France Vakgroep Biochemie Fysiologie en Microbiologie Gent Belgium Laborat. de Spectrométrie de Masse Bioorganique URA 31 CNRS Université Louis Pasteur Strasbourg Cedex France Sterling winthrop Inc. Collegeville Lexin Pharmaceutical Corporation Horsham PerSeptive Biosystems Houston Parke-Davis Pharmaceutical Research Division of Warner Lambert Company Ann Arbor Dept. of Chemistry The Ohio State University Columbus USA Dept. of Biochemistry Dalhousie University Halifax Canada Biomedical Research Center University of British Columbia Vancouver Canada Dept. of Biochem. & Molec. Biol. Univ. of Miami Sch. of Medicine Miami The Rockefeller Institute New York Dept. of Cell Biol. & Anat. Univ. of Miami Sch. of Medicine Miami Biosciences Laboratory 3M Co. St. Paul Pittsburgh Supercomputing Center Pittsburgh Department of Molecular Genetics/Biochemistry University of Pittsburgh Pittsburgh Dept. Biochem. and Mol. Biol. University of Florida Gainesville U.S. Environmental Protection Agency Gulf Breeze Dept. Zoology North Carolina State University Raleigh PerSeptive Biosystems Inc. Cambridge Department of Chemistry Univ

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INFERENTIAL MODEL-BASED control OF MULTICOMPONENT BATCH DISTILLATION

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chemical engineering SCIENCE 1992年第4期47卷 887-898页

作者： QUINTEROMARMOL, E LUYBEN, WL Process Modeling and Control Center Department of Chemical Engineering Mountaintop Campus 111 Research Drive Lehigh University Bethlehem PA 18015 U.S.A.

Industrial interest in batch distillation has increased significantly in recent years as more batch processing is being used for low-volume high-value specialty chemicals. Most studies have concentrated on the determination of optimum operating strategies: optimum trajectories of reflux ratio and pressure during the batch and processing of the slop cuts that are produced. Little attention has been paid to the problems of control. If instantaneous and perfect analyzers were available, the control of batch distillation would be straightforward once the optimum policies are available. Switching from total-reflux operation to producing product and from this to slop-cut production could be performed when compositions in the reflux drum or in product tankage reached the desired values. However, in most industrial applications of batch distillation, perfect composition measurements are not available. This means that an inferential control system that relies on temperature and flow measurements must be used. Models of the batch distillation process can be used to provide estimates of the required compositions. This paper presents the results of a study of two types of model-based inferential control systems for multicomponent batch distillation. The results showed that both steady-state and dynamic estimators provide good estimation of the distillate compositions using only one temperature measurement.

关键词： Distillation columns

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