Abstract
A definition of virtual analyzers as software algorithmic systems generating models in real time on the basis of current and retrospective information about the industrial processes was given. Methods of development of the virtual analyzers were presented, as well as examples of their industrial applications.
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REFERENCES
Dubinin, V.A., Informatsionnyi menedzhment--fantom, obretayushchii plot' (Information Management is a Phantom Assuming Flesh), Moscow: Planeta KIS, 2001.
Kulikov, V.N., Strategy of Development of the Industrial Information Technologies, Mir Komp'yuternoi Avtomatizatsii, 2001, no. 4, pp. 12–15.
Afanas'ev, V.N. and Postnikov, A.I., Informatsionnye tekhnologii v upravlenii predpriyatiem (Information Technologies in Industrial Control), Moscow: MGIEM, 2003.
Hoske, M.T., How to Integrate Software, Control Engineering, 2000, no. 11.
Nesterova, A., MES--Industrial Control Systems. Make use of Evident Advantages, Mir Komp'yuternoi Avtomatizatsii, 2001, no. 4, pp. 24–26.
Musaev, A.A., Virtual Analyzers: The Concept of Design and Use in the Problems of Continuous Process Control, Avtomatiz. Promyshl., 2003, no. 8, pp. 28–33.
Harrold, D., Process Control's Latest Tool: Soft Sensors, Control Eng. Eur., June/July 2001, pp. 42–45.
Ljung, L., System Identification: Theory for the User, Englewood Cliffs: Prentice Hall, 1987. Translated under the title Identifikatsiya sistem. Teoriya dlya pol'zovatelya, Moscow: Nauka, 1991.
Sorkin, L.R., Achievements of the Trapeznikov Institute of Control Sciences in the Development and Introduction of the Information Control Technologies in the Oil and Gas System, in: Plenarnye dokl. Mezhdunar. konf. po problemam upravleniya (Int. Conf. on Control. Plenary Papers), Moscow: Inst. Probl. Upravlen., 1999, pp. 172–179.
Dozortsev, V.M., Kneller, D.V., and Levit, M.Yu., On Adequacy of the Process Simulators, in: Plenarnye dokl. Mezhdunar. konf. "Identifikatsiya sistem i zadachi upravleniya" (Pleanry Papers. Int. Conf. "System Identification and Control Problems"), Moscow: Inst. Probl. Upravlen., 2000.
Tumanov, N.A., Tumanov, D.N., Chadeev, V.M., and Bakhtadze, N.N., Virtual Analyzer-Based Control Systems for Production of Mineral Fertilizers, Avtomatiz. Promyshl., 2003, no. 8, pp. 33–36.
Osnovy upravleniya tekhnologicheskimi protsessami (Process Control Fundamentals), Raibman, N.C., Ed., Moscow: Nauka, 1978.
Tsypkinh, Ya.Z., Control of Dynamic Objects under Bounded Uncertainty, Izmereniya, Kontrol', Avtomatizatsiya, 1991, no. 3–4, pp. 3–21.
Fomin, V.N., Fradkov, A.L., and Yakubovich, V.A., Adaptivnoe upravlenie dinamicheskimi ob"ektami (Adaptive Control of Dynamic Objects), Moscow: Nauka, 1981.
Bartos, F.J., Artificial Intelligence: Smart Thinking for Complex Control, Control Eng., 1997, no. 7.
Zadeh, L.A., Fuzzy Sets and Applications, New York: Wiley, 1987.
Zadeh, L.A., Fuzzy Sets, Inform. Control, 1965, no. 6, pp. 338–353.
Zadeh, L.A., Outline of a New Approach to the Analysis of Complex Systems and Decision Processes, IEEE Trans. Syst. Man Cybernetics, 1973, no. 1, pp. 28–44.
Masalovich, A.I., Computer... Predicts, Softmarket, 1996, no. 23, pp. 6–9.
Nechetkie mnozhestva v modelyakh upravleniya i iskusstvennogo intellekta (Fuzzy Sets in Models of Control and Atrificial Intelligence), Pospelov, D.A., Ed., Moscow: Nauka, 1986.
Kosko, B., Fuzzy Thinking, New York: Hyperion, 1992.
Kosko, B., Neural Networks and Fuzzy Systems. A Dynamic System Approach to Machine Intelligence, New Jercey: Prentice Hall, 1992.
Zemankova-Leech, M. and Kandel, A., Fuzzy Relational Data Bases: A Key to Expert Systems, Cologne: TUV Rheinland, 1984.
Karpenko, A.S., Multivalued Logics, Logika Komp'yuter, 1997, no. 4.
McNeill, D. and Freiberger, P., Fuzzy Logic, New York: Simon and Schuster, 1993.
Shtovba, S.D., Introduction to the Fuzzy Set Theory and Fuzzy Logic, in: Tez. dokl. Vseros. nauch. konf. "Proektirovanie nauchnykh and inzhenernykh prilozhenii v srede MATLAB" (Abstracts of Paper Russian Conf. "Design of Scientific and Engineering Applications in the MATLAB Environment"), Moscow: Inst. Probl. Upravlen., 2002.
Mamdani, E.H., Application of Fuzzy Algorithms for the Control of a Simple Dynamic Plant, Proc. IEEE, 1974, vol. 121, pp. 371–378.
Kutukov, S.E. and Vasil'ev, V.I., Elements of Artificial Intelligence in Systems of Collection, Preparation, and Transportation of Hydrocarbon Materials (http://www.ogbus.ru/authors/kutukov/kuts.pdf).
Gorban', A.N., Vozmozhnosti neironnykh setei. Neiroinformatika (Potentialities of the Neural Networks. Neural informatics), Novosibirsk: Nauka, 1998.
Blum, F., Leiserson, A., and Hofstedter L., A Brain, Mind and Behavior, Moscow: Mir, 1988, pp. 53–80.
Makhotilo, K.V., Analysis of Parametric Sensitivity of the Neural Network Control System, Tr. Mezhdunar. nauch.-tekh. konf. "MicroCAD'97," Inform. tekhnologii: nauka, tekhnika, tekhnologiya, obrazovanie, zdorov'e (Proc. Int. Conf. "microCAD'97," Information Technologies, Education, Health), Khar'kov: KHGPU, 1997, pp. 137–141.
Kashchavtsev, S., Personal Intelligence, Komp'yuterra, 2002, no. 20.
Galushkin, A.I., Current Directions of Development of the Neural Computer Technologies in Russia, Otkrytye Sistemy, 1997.
McCulloch, W.W. and Pitts, W., A Logical Calculus of the Ideas Imminent in Nervous Activity, Bulletin of Mathematical Biophysics, 1943, no. 5, pp. 115-33. Translated in Avtomaty, Shannon, C.E. and McCarthy, J.M., Eds., Moscow: Inostrannaya Literatura, 1956, pp. 362–384.
Rosenblatt, F., Principles of Neurodynamics, New York: Spartan Books, 1962. Translated under the title Printsipy neirodinamiki, Moscow: Mir, 1965.
Minsky, M. and Papert, S., Perceptrons, Cambridge: MIT Press, 1969. Translated under the title Perseptrony, Moscow: Mir, 1971.
Galushkin, A.I. and Logovskii, A.S., Neural Control: Basic Principles and Directions of Application of Neural Computers for Solution of Problems of Dynamic Plant Control, Dokl. Mezhdunar. konf. po problemam upravleniya (Proc. Int. Conf. on Control), Moscow: Inst. Probl. Upravlen., 1999.
Rumelhart, D.E., Hinton, G.E., and Williams, R.G., Learning Representation by Back-propagating Error, Nature, 1986, vol. 323, no. 6088, pp. 533–536.
Aved'yan, E.D., Barkan, G.V., and Levin, I.K., Cascaded Neural Networks, Avtom. Telemekh., 1999, no. 3, pp. 38–55.
Koposov, A.I., Shcherbakov, I.B., and Kislenko, N.A., Creating an Analytical Review of the Information Sources on Application of Neural Networks for Gas Technology. Research Report, Moscow: VNIIGAZ, 1995.
Hecht-Nilsen, R., Neurocomputing: Picking the Human Brain, IEEE Spectrum, 1998, vol. 25, no. 3, pp. 36–41.
Holland, J., Adaptation in Natural and Artificial Systems. Adaptation in Natural and Artificial Systems, Ann Arbor: Univ. Michigan, 1992.
Booker, L.B., Goldberg, D.E., and Holland, J.H., Classifier Systems and Genetic Algorithms, Artificial Intelligence, 1989, vol. 40, no. 2, pp. 235–282.
Goldberg, D., Genetic Algorithms in Machine Learning, Optimization and Search, Massachusetts: Addison-Wesley, 1989.
Jones, A.J., Genetic Algorithms and Their Applications to the Design of Neural Network, Neural Computing Applications, 1993, vol. 1, no. 1.
Bunich, A.L. and Bakhtadze, N.N., Sintez i primenenie adaptivnykh sistem s identifikatorom (Design and Use of Adaptive Systems with Identifier), Moscow: Nauka, 2003.
Kurzhanskii, A.B., Upravlenie i nablyudenie v usloviyakh neopredelennosti (Control and Observation under Uncertainty), Moscow: Nauka, 1977.
Chernous'ko, F.L., Otsenivanie fazovogo sostoyaniya dinamicheskikh sistem. Metod ellipsoidov (Estimation of the Phase State of Dynamic Control. Ellipsoid method), Moscow: Nauka, 1988.
Tsypkinh, Ya.Z., Informatsionnaya teoriya identifikatsii (Information Theory of Identification), Moscow: Nauka, 1995.
Soderstrom, T. and Stoica, P., Variable Methods for System Identification New York: Springer, 1983.
Tertychnyi, V.Yu., Stokhasticheskaya mekhanika (Stochastic Mechanics), Moscow: Faktorial Press, 2001.
Grigor'ev, F.N., Kuznetsov, N.A., and Serebrovskii, A.P., Upravlenie nablyudeniyami v avtomaticheskikh sistemakh (Control of Observations in Automatic Systems), Moscow: Nauka, 1986.
Krasovskii, A.A., Historical Review and State-of-the-Art of the Fundamental Applied Science of Control as Exemplified by the Self-organizing Controllers, Plenarnye dokl. Mezhdunar. konf. po problemam upravleniya (Int. Conf. on Control, Plenary Papers), Moscow: Inst. Probl. Upravlen., 1999, pp. 4–23.
Polyak, B.T., Trudy Inst. Probl. Upravlen., 1999, vol. 5, pp. 36–41.
Semenov, A.V., Osnovy H∞-teorii upravleniya. Kurs lektsii (Fundamentals of the H∞-theory of Control. Lectures), Moscow: GOSNIIAS, 1992.
Andronov, A.A. and Pontryagin, L.S., Rough Systems, Dokl. Akad. Nauk SSSR, 1937, vol. 14, no. 5, pp. 247–249.
Huber, P.J., Robust Statistics, New York: Wiley, 1981. Translated under the title Robastnost' v statistike, Moscow: Mir, 1984.
Tsypkin, Ya.Z. and Polyak, B.T., Robust Stability of Linear Discrete Systems, Dokl. Akad. Nauk SSSR, 1991, vol. 316, no. 4, pp. 842–846.
Tsypkin, Ya.Z., Robustness in System of Control and Data Processing, Avtom. Telemekh., 1992, no. 1, pp. 165–169.
Dzhuri, E., Robustness of Discrete Systems, Avtom. Telemekh., 1990, no. 5, pp. 3–28.
Tsypkin, Ya.Z. and Polyak, B.T., Frequency Methods of Robust Stability of Linear Discrete Systems, Avtomatika, 1990, no. 4, pp. 3–9.
Polyak, B.T. and Tsypkin, Ya.Z., Frequency Methods of Robust Stability and Aperiodicity of Linear Systems, Avtom. Telemekh., 1990, no. 9, pp. 45–54.
Tsypkin, Ya.Z., Stochastic Discrete Systems with Internal Models, Probl. Upravlen. Inf., 1996, no. 12, pp. 21–25.
Kurdyukov, A.P., Osnovy robastnogo upravleniya (Fundamentals of Robust Control), Moscow: Mosk. Gos. Tekhn. Univ., 1995.
Petrov, B.I., Rutkovskii, V.Yu., and Zemlyakov, S.D., Adaptivnoe koordinatno-parametricheskoe upravlenie nestatsionarnymi ob"ektami (Adaptive Coordinate-Parametric Control of Nonstationary Objects), Moscow: Nauka, 1980
Zemlyakov, S.D. and Rutkovskii, V.Yu., Adaptation Algorithms and Conditions for Operability of the Self-adjusting Control System of a Multivariable Plant with Variable Parameters, Avtom. Telemekh., 1981, no. 1, pp. 65–73.
Pavlov, B.V., Structural Design of the Main Loop of Searchless Self-adjusting Systems, Avtom. Telemekh., 1977, no. 12, pp. 56–64.
Yadykin, I.B., Shumskii, V.M., and Ovsepyan, F.A., Adaptivnoe upravlenie nepreryvnymi tekhnologich-eskimi protsessami (Adaptive Control of Continuous Processes), Moscow: Energoatomizdat, 1985.
Bukov, V.N., Adaptivnye prognoziruyushchie sistemy upravleniya poletom (Adaptive Predicting Flight Control Systems), Moscow: Nauka, 1987.
Afanas'ev, V.N., Kolmanovskii, V.B., and Nosov, V.R., Matematicheskaya teoriya konstruirovaniya sistem upravleniya (Mathematical Theory of Control System Design), Moscow: Vysshaya Shkola, 2003.
Derevitskii, D.P. and Fradkov, A.L., Prikladnaya teoriya diskretnykh adaptivnykh sistem upravleniya (Applied Theory of Discrete Adaptive Control Systems), Moscow: Nauka, 1981.
Nazin, A.V., Adaptivnyi vybor variantov: Rekkurentnye algoritmy (Adaptive Choice of Variants: Recurrent Algorithms), Moscow: Nauka, 1986.
Kurdyukov, A.P., Design of Optimal Robust Controllers under Disturbances, in: Metody klassicheskoi i sovremennoi teorii upravleniya (Methods of the Classical and Modern Control Theory), Moscow: Mosk. Gos. Tekhn. Univ., 2000.
Doyle, J., Analysis of Feedback Systems with Strustured Uncertainties, IEEE Proc., 1982, vol. 129, part D, no. 6.
Stein, G. and Doyle, J., Beyond Singular Values and Loop Shapes, J. Guidance, 1991, vol. 14, no. 1.
Packard, A. and Doyle, J., The Complex Structured Singular Value, Automatica, 1993, vol. 29, no. 1.
Packard, A. and Doyle, J., Quadratic Stability with Real and Complex Perturbations, IEEE Trans. Automat. Control, vol. 35, no. 2.
Lu, W.M., Zhou, K., and Doyle J., Stabilization of LFTnsystems, Proc. 30 CDC, Brihton, 1991.
Vidyasagar, M., Optimal Rejection of Persistent Bounded Disturbances, IEEE Trans. Automat. Control, 1986, vol. 31, pp. 527–534.
Khammash, M. and Pearson, J.B., Perfomance Robustness of Discrete-time Systems with Structured Uncertainty, IEEE Trans. Automat. Control, 1991, vol. 36, no. 4.
Dahleh, M.A. and Khammash, M.H., Controller Design for Plants with Structured Uncertainty, Automatica, 1993, vol. 29, no. 1.
Chappelat, H. and Bhattacharya, S.P., A Generalization of Kharitonov's Theorem: Robust Stability of Interval Plants, IEEE Trans. Automat. Control, 1989, vol. 34, no. 3.
Hollot, C.V. and Yang, F., Robust Stabilization of Interval Plants Using Lead or Lag Compensators, Syst. Control. Lett., 1990, vol. 14, no. 1.
Petersen, I.R., A New Extention of Kharitonov's Theorem, IEEE Trans. Automat. Control, 1990, vol. 35, no. 7.
Barmish, B.R. and Kang, H.I., Extreme Point Results for Robust Stability of Interval Plants: Beyond First Order Compensators, Proc. FirstIFACSymp. OnDes. Meth.Control Sys., ETH, Zurich, 1991, vol. 1, pp. 1–16.
Semyonov, A.V., Vladimirov, I.G., and Kurdjukov, A.P., Stochastic Approach to H∞-optimization, Proc. 33rd Conf. Decision and Control, Florida, vol. 3, 1994.
Vladimirov, I.G., Kurdyukov, A.P., and Semenov, A.V., Stochastic Problem of H∞-optimization, Dokl. Ross. Akad. Nauk, 1995, no. 5, pp. 343–350.
Vladimirov, I.G., Kurdyukov, A.P., and Semenov, A.V., Asymptotics of the Anisotropic Norm of Linear Stationary Systems, Avtom. Telemekh., 1999, no. 3, pp. 78–87.
Polyak, B.T. and Kiselev, O.N., Design of Low-order Controllers by the H∞-Criterion and the Criterion for Maximum Robustness, Avtom. Telemekh., 1999, no. 3, pp. 119–130.
Tsypkin, Ya.Z., Design of Robust-optimal Plant Control Systems under Bounded Uncertainty, Avtom. Telemekh., 1992, no. 9, pp. 139–159.
Tsypkin, Ya.Z., Robust-optimal Discrete Control Systems, Avtom. Telemekh., 1999, no. 3, pp. 25–37.
Barabanov, A.E. and Granichin, O.N., Optimal Controller of a Linear Plant with Bounded Noise, Avtom. Telemekh., 1984, no. 5, pp. 39–46.
http://www.umich.edu/flash.html
Bakhtadze, N.N., Lototskii, V.A., and Fayans, M.A., Identification Approach to Investment Planning, Tr. Mezhdunar. konf. "Identifikatsiya sistem i zadachi upravleniya" (Proc. Int. Conf. "System Identification and Problems of Control"), Moscow: Inst. Probl. Upravlen., 2000, pp. 9–14.
Bakhtadze, N.N. and Nazin, A.V., Virtual Analyzer in the Systems of Company Debt Management, Tez. dokl. 2-i Mezhdunar. konf. po problemam upravleniya (Second Int. Control Conf.), Moscow: Inst. Probl. Upravlen., vol. 2, p. 4, 2003.
Lototskii, V.A. and Mandel', A.S., Modeli i metody upravleniya zapasami (Models and Methods of Inventory Control), Moscow: Nauka, 1991.
Bobrovskii, S.A., Outlooks and Tendencies of Artificial Intelligence, PC Week/RE, 2001, no. 32, p. 32.
Masterenko, D.A., Recurrent Robust Estimation in Computerized Information-and-Measurement Systems, Tez. dokl. nauchno-tekhn. konf. "Sostoyanie i problemy tekhnicheskikh izmerenii" (Second Conf. "State-of-the-Art and Problems of Technical Measurements"), Moscow: Mosk. Gos. Tekhn. Univ., 1995.
Gorbunov, A.R., Upravlenie finansovymi potokami (Management of Financial Flows), Moscow: Toratsentr, 2003.
Kardash, V.A., Modeli upravleniya proizvodstvenno-ekonomicheskimi protsessami v sel'skom khozyaistve (Models of Control of Production and Economics in Agriculture), Moscow: Ekonomika, 1981.
Prokopchina, S.V., Bayes Integrating Technologies based on Intelligent and Soft Measurements, in Dokl. konf. SCM'99 (Proc. Conf. SCM'99), St. Petersburg, 1999, pp. 25–32.
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Bakhtadze, N.N. Virtual Analyzers: Identification Approach. Automation and Remote Control 65, 1691–1709 (2004). https://doi.org/10.1023/B:AURC.0000047885.52816.c7
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DOI: https://doi.org/10.1023/B:AURC.0000047885.52816.c7