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European control Conference (ECC)

作者： Jiusun Zeng Lei Xie Uwe Kruger Jie Yu Jingjing Sha Xuyi Fu College of Metrology & Measurement Engineering China Jiliang University Hangzhou China Institute of Cyber Systems & Control Zhejiang University Hangzhou China Department of Mechanical and Industrial Engineering Sultan Oaboos University Sultanate of Oman Department of Chemical Engineering McMaster University Hamilton Canada

This article proposes to monitor industrial process faults using Kullback Leibler (KL) divergence. The main idea is to measure the difference between the distributions of normal and faulty data. Sensitivity analysis on the KL divergence under Gaussian distribution assumption is performed, which shows that the sensitivity of KL divergence increases with the number of samples. For non-Gaussian data, a recently proposed kernel method for density ratio estimation is used to estimate the KL divergence. The density ratio estimation method does not involve direct estimation of probability density functions, hence is fast and efficient. For monitoring of non-Gaussian data, the confidence limits are obtained through a window based strategy. Application studies involving a simulation example and an industrial melter process show that the performance of the proposed monitoring strategy is better than the principal component analysis (PCA) based statistical local approach.

关键词： Monitoring Estimation Principal component analysis Kernel Sensitivity Probability density function Educational institutions

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A moving horizon approach to multivariable input design in general linear systems with constraints

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IFAC Proceedings Volumes 2013年第32期46卷 577-582页

作者： R.S. Patwardhan R.B. Gopaluni Process and Control Systems Department Saudi Aramco Dhahran Saudi Arabia 31311 Department of Chemical and Biological Engineering University of British Columbia Vancouver BC Canada V6T 1Z4

The quality of a model determines the closed loop performance of model predictive controllers. However, identification of high quality multivariable models is a time and energy intensive exercise. The industrial model predictive controllers are designed using large dimensional multivariable models and they are often identified using ad-hoc single input bump tests. A novel multivariable input design approach is developed using a modified model predictive control objective function. It is shown that the proposed input design approach is trace optimal with respect to the covariance of model parameters. The approach is shown to work well in closed loop on both well and ill-conditioned processes even under model-plant mismatch while meeting input and output constraints.

关键词： Input design closed loop systems model predictive control

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Rheological, viscoelastic and vulcanization study of sponge EPDM/NBR blendednano-composites

Rheological, viscoelastic and vulcanization study of sponge ...

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International Conference on Nanoscience & Technology,China 2013(ChinaNANO 2013)

作者： Mohammad Arshad Bashir Muhammad Shahid Riaz Ahmed School of Chemical and Materials Engineering National University of Sciences & Technology Islamabad Pakistan Institute of Industrial Control Systems P. O. Box 1398 Rawalpindi Pakistan

The present research reports the effect of variant blending ratio of Ethylene Propylene Diene Monomer and Nitrile Butadiene Rubber (EPDM/NBR) on the, rheology, curing behaviour, tangent δ, viscosity variation during vulcanization of polymer sponge nanocomposites. The purpose of this study is to develop high strength foamy structure polymer composites with the blending ratio of the base polymers along with the carbon nano particles for damping and high energy absorbing applications. It is observed that the rheology, vulcanization and viscoelastic nature of the fabricated composites are efficiently influenced with the progressive variation of blending ratio of rubber matrix.

关键词： EPDM, Nano-Composites, Vulcanization, Curing behavior, Rheology

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Fungal diversity notes 253-366:taxonomic and phylogenetic contributions to fungal taxa

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Fungal Diversity 2016年第3期78卷 1-237页

作者： Guo Jie Li Kevin D.Hyde Rui Lin Zhao Sinang Hongsanan Faten Awad Abdel-Aziz Mohamed A.Abdel-Wahab Pablo Alvarado Genivaldo Alves-Silva Joseph F.Ammirati Hiran A.Ariyawansa Abhishek Baghela Ali Hassan Bahkali Michael Beug D.Jayarama Bhat Dimitar Bojantchev Thitiya Boonpratuang Timur S.Bulgakov Erio Camporesi Marcela CBoro Oldriska Ceska Dyutiparna Chakraborty Jia Jia Chen K.W.Thilini Chethana Putarak Chomnunti Giovanni Consiglio Bao Kai Cui Dong Qin Dai Yu Cheng Dai Dinushani A.Daranagama Kanad Das Monika C.Dayarathne Eske De Crop Rafael J.V.De Oliveira Carlos Alberto Fragoso de Souza JoséIde Souza Bryn T.M.Dentinger Asha J.Dissanayake Mingkwan Doilom E.Ricardo Drechsler-Santos Masoomeh Ghobad-Nejhad Sean P.Gilmore Aristóteles Góes-Neto MichałGorczak Charles H.Haitjema Kalani Kanchana Hapuarachchi Akira Hashimoto Mao Qiang He John K.Henske Kazuyuki Hirayama Maria J.Iribarren Subashini C.Jayasiri Ruvishika S.Jayawardena Sun Jeong Jeon Gustavo H.Jerônimo Ana L.Jesus E.B.Gareth Jones Ji Chuan Kang Samantha C.Karunarathna Paul M.Kirk Sirinapa Konta Eric Kuhnert Ewald Langer Haeng Sub Lee Hyang Burm Lee Wen Jing Li Xing Hong Li Kare Liimatainen Diogo Xavier Lima Chuan Gen Lin Jian Kui Liu Xings Zhong Liu Zuo Yi Liu J.Jennifer Luangsa-ard Robert Lücking H.Thorsten Lumbsch Saisamorn Lumyong Eduardo M.Leaño Agostina V.Marano Misato Matsumura Eric H.C.McKenzie Suchada Mongkolsamrit Peter E.Mortimer Thi Thuong Thuong Nguyen Tuula Niskanen Chada Norphanphoun Michelle A.O’Malley Sittiporn Parnmen Julia Pawłowska Rekhani H.Perera Rungtiwa Phookamsak Chayanard Phukhamsakda Carmen L.A.Pires-Zottarelli Olivier Raspé Mateus A.Reck Sarah C.O.Rocha AndréL.C.M.Ade Santiago Indunil C.Senanayake Ledo Setti Qiu Ju Shang Sanjay K.Singh Esteban B.Sir Kevin V.Solomon Jie Song Prasert Srikitikulchai Marc Stadler Satinee Suetrong Hayato Takahashi Takumasa Takahashi Kazuaki Tanaka Li Ping Tang Kasun M.Thambugala Donnaya Thanakitpipattana Michael K.Theodorou Benjarong Thongbai Tuksaporn Thummarukcharoen Qing Tian Saowaluck Tibpromma Annemieke State Key Laboratory of Mycology Institute of MicrobiologyChinese Academy of SciencesNo 31st West Beichen RoadChaoyang DistrictBeijing 100101People’s Republic of China Centre of Excellence in Fungal Research and School of Science Mae Fah Luang UniversityChiang Rai 57100Thailand Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China Department of Botany and Microbiology College of ScienceKing Saud UniversityP.O.Box:2455Riyadh 1145Saudi Arabia Department of Botany and Microbiology Faculty of ScienceSohag UniversitySohag 82524Egypt ALVALAB C/La Rochela nº47E-39012 SantanderSpain Micolab Programa de Pós-Graduação em Biologia de FungosAlgas e PlantasDepartamento de BotânicaUniversidade Federal de Santa CatarinaCampus Universitário TrindadeCEP:88040-900 FlorianópolisSanta CatarinaBrazil Department of Biology University of WashingtonBox 351800SeattleWA 98195-1800USA Guizhou Key Laboratory of Agricultural Biotechnology Guizhou Academy of Agricultural SciencesGuiyang 550006GuizhouPeople’s Republic of China National Fungal Culture Collection of India(NFCCI) Biodiversity and Palaeobiology GroupMACS’Agharkar Research InstituteG.G.Agarkar RoadPune 411004India PO Box 116 HusumWA 98623-0116USA Formerly Department of BotanyGoa UniversityGoaIndia No.128/1-J Azad Housing SocietyCurcaP.O.Goa Velha 403108India *** 345 Shipwatch LaneHerculesCA 94547USA Microbe Interaction Laboratory(BMIT) BIOTECNational Science and Technology Development Agency(NSTDA)113 Thailand Science ParkThanon PhahonyothinTombon Khlong NuengAmphoeKhlong LuangPathum Thani 12120Thailand Academy of Biology and Biotechnology Southern Federal UniversityRostov-on-Don 344090Rostov regionRussia A.M.B.Gruppo Micologico Forlivese BAntonio“Cicognani” Via Roma Forlì Italy 18 A.M.B.Circolo Micologico“Giovanni Carini”C.P.314BresciaItaly Societàper gli Studi Naturalistici della Romagna C.P.144Bagnacavallo

Notes on 113 fungal taxa are compiled in this paper,including 11 new genera,89 new species,one new subspecies,three new combinations and seven reference *** geographic and taxonomic range of fungal taxa are *** the Ascomycota the new genera Angustospora(Testudinaceae),Camporesia(Xylariaceae),Clematidis,Crassiparies(Pleosporales genera incertae sedis),Farasanispora,Longiostiolum(Pleosporales genera incertae sedis),Multilocularia(Parabambusicolaceae),Neophaeocryptopus(Dothideaceae),Parameliola(Pleosporales genera incertae sedis),and Towyspora(Lentitheciaceae)are *** introduced species are Angustospora nilensis,Aniptodera aquibella,Annulohypoxylon albidiscum,Astrocystis thailandica,Camporesia sambuci,Clematidis italica,Colletotrichum menispermi,***,Comoclathris pimpinellae,Crassiparies quadrisporus,Cytospora salicicola,Diatrype thailandica,Dothiorella rhamni,Durotheca macrostroma,Farasanispora avicenniae,Halorosellinia rhizophorae,Humicola koreana,Hypoxylon lilloi,Kirschsteiniothelia tectonae,Lindgomyces okinawaensis,Longiostiolum tectonae,Lophiostoma pseudoarmatisporum,Moelleriella phukhiaoensis,***,Mucoharknessia anthoxanthi,Multilocularia bambusae,Multiseptospora thysanolaenae,Neophaeocryptopus cytisi,Ocellularia arachchigei,***,Ochronectria thailandica,Ophiocordyceps karstii,Parameliola acaciae,***,Parastagonospora cumpignensis,Pseudodidymosphaeria phlei,Polyplosphaeria thailandica,Pseudolachnella brevifusiformis,Psiloglonium macrosporum,Rhabdodiscus albodenticulatus,Rosellinia chiangmaiensis,Saccothecium rubi,Seimatosporium pseudocornii,***,Sigarispora ononidis and Towyspora *** combinations are provided for Eutiarosporella dactylidis(sexual morph described and illus trated)and Pseudocamarosporium ***,illustrations and/or reference specimens are designated for Aposphaeria corallinolutea,Cryptovalsa ampelina,Dothiorella vidmadera,Ophiocordyceps formosana,P

关键词： Ascomycota Basidiomycota Neocallimastigomycota Oomycota.Zygomycota Phylogeny Taxonomy New genus New species

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GNURadio, Scilab, Xcos and COMEDI for data acquisition and control: An open source alternative to labVIEW

GNURadio, Scilab, Xcos and COMEDI for data acquisition and c...

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8th International Symposium on Advanced control of chemical Processes, ADCHEM 2012

作者： Patil, Jagdish Y. Dubey, Balashish Moudgalya, Kannan M. Peter, Rakesh Department of Systems and Control Engineering IIT Bombay Mumbai 400076 India Department of Chemical Engineering IIT Bombay Mumbai 400076 India Department of Chemical Engineering and Systems and Control Engineering IIT Bombay Mumbai 400076 India Dept. of Computer Science Amrita University Coimbatore India

ISBN: (纸本)9783902823052

This article describes an attempt to create an open source equivalent to the data acquisition and control software LabVIEW. The proposed solution uses GNURadio, OpenCV, Scilab, Xcos and COMEDI on Linux. GNURadio gives a convenient graphical front end. The computations can be carried out using OpenCV or Scilab and Xcos. The device drivers given in COMEDI are used to access real time data. We also present PyGTK based improved graphical user interface for GNURadio. © 2012 IFAC.

关键词： Graphical user interfaces

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Optimal batch process regulation using self-optimizing control, NCO tracking

Optimal batch process regulation using self-optimizing contr...

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8th International Symposium on Advanced control of chemical Processes, ADCHEM 2012

作者： Singhal, Martand Gudi, Ravindra D. Department of Systems and Control Engineering Indian Institute of Technology Bombay Mumbai 400076 India Department of Chemical Engineering Indian Institute of Technology Bombay Mumbai 400076 India

ISBN: (纸本)9783902823052

Optimal operation of batch processes in the presence of uncertainty has been an area of significant research interest. The use of online measurements as a source of information offers scope to mitigate the effects of uncertainty and attain optimal operation. Therefore, amongst the different approaches proposed to address the uncertainty issues, measurement based optimization approaches have been shown to be eminently suited. Measurements have been broadly used in two approaches, viz. self optimizing control (SOC) and tracking of necessary conditions of optimality (NCO). In an earlier work for continuous processes by Jaschke and Skogestad [1], the relative complementary roles of NCO tracking and SOC were clearly highlighted in terms of their applicability in combating the effects of different scales of uncertainty and disturbances. For batch processes, the NCO tracking is found to be successful, the complementary role of SOC is largely un-explored. In this work, we extend the integrated approach of Jaschke and Skogestad [1] to batch processes by redefining the NCO and SOC layers. The proposed framework is evaluated using simulations involving a nonlinear batch polymerization of styrene. © 2012 IFAC.

关键词： Polymerization

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Explicit-model predictive control: A simulation based scalability study

Explicit-model predictive control: A simulation based scalab...

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8th International Symposium on Advanced control of chemical Processes, ADCHEM 2012

作者： Gupta, Arun Bhartiya, Sharad Nataraj, P.S.V. ABB-GISL Research Bangalore 560048 India Department of Chemical Engineering IIT Bombay Mumbai India Department of Systems and Control Engineering IIT Bombay Mumbai India

ISBN: (纸本)9783902823052

The main impediment in the applicability of explicit model predictive control (e-MPC) is that the number of regions in the parametric space increases dramatically with an increase in the dimension of the parameter and decision spaces as well as with an increase in the number of constraints. This work explores the scalability issues by simulation in which e-MPC is used for control of quadruple tank system. Explicit- MPC problem formulation from a standard MPC (for finite and infinite prediction horizon) using multi parametric quadratic programming (mp-QP) is presented. The results confirm that while the number of critical regions increases exponentially with the control horizon, the online calculations are computationally inexpensive. © 2012 IFAC.

关键词： Scalability

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Plant friendly input design for system identification in closed loop

Plant friendly input design for system identification in clo...

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Universite Libre de Bruxelles

作者： Narasimhan, Sridharakumar Bombois, Xavier Dept. of Chemical Engineering IIT Madras Chennai India Delft Center for Systems and Control Delft University of Technology Netherlands

ISBN: (纸本)9783902823069

Optimal experiment or input design is the scientific exercise of designing informative excitation signals for the identification of a real-life dynamic system. In the least costly input design framework, the input is designed such that the identification cost is minimized while meeting desired specifications on the quality of the identified model. Identification of real-life processes require that the identification be "plant-friendly". These are typically imposed as constraints on experiment time, input and output amplitudes or input move sizes. This work focusses on an LMI based plant friendly input design in the least costly framework. © 2012 IFAC.

关键词： Convex optimization

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GNURadio, Scilab, Xcos and COMEDI for Data Acquisition and control: An Open Source Alternative to LabVIEW *

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IFAC Proceedings Volumes 2012年第15期45卷 626-631页

作者： Jagdish Y. Patil Balashish Dubey Kannan M. Moudgalya Rakesh Peter Systems & Control Engineering IIT Bombay Mumbai 400076 Chemical Engineering IIT Bombay Mumbai 400076 Chemical Engineering and Systems & Control Engineering IIT Bombay Mumbai 400076 Dept. of Computer Science Amrita University Coimbatore

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Optimal Batch Process Regulation using Self-optimizing control, NCO tracking

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IFAC Proceedings Volumes 2012年第15期45卷 81-86页

作者： Martand Singhal Ravindra D. Gudi Systems and Control Engineering Indian Institute of Technology Bombay Mumbai 400076 India Department of Chemical Engineering Indian Institute of Technology Bombay Mumbai 400076 India

Optimal operation of batch processes in the presence of uncertainty has been an area of significant research interest. The use of online measurements as a source of information offers scope to mitigate the effects of uncertainty and attain optimal operation. Therefore, amongst the different approaches proposed to address the uncertainty issues, measurement based optimization approaches have been shown to be eminently suited. Measurements have been broadly used in two approaches, viz. self optimizing control (SOC) and tracking of necessary conditions of optimality (NCO). In an earlier work for continuous processes by Jäschke and Skogestad [1], the relative complementary roles of NCO tracking and SOC were clearly highlighted in terms of their applicability in combating the effects of different scales of uncertainty and disturbances. For batch processes, the NCO tracking is found to be successful, the complementary role of SOC is largely un-explored. In this work, we extend the integrated approach of Jäschke and Skogestad [1] to batch processes by redefining the NCO and SOC layers. The proposed framework is evaluated using simulations involving a nonlinear batch polymerization of styrene.

关键词： Constraint Tracking Dynamic Optimization Necessary Conditions of Optimality Polymerization Self Optimizing control

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