Keywords
fuzzy modeling algorithm
undefined points of operation
Kawamoto non-linearity sectors
nonlinear MIMO systems
Takagi-Sugeno-Kang
undefined points of operation
Kawamoto non-linearity sectors
nonlinear MIMO systems
Takagi-Sugeno-Kang
How to Cite
Gonzalez, L. (2023). Algorithm for Diffuse TSK Modeling of SNL MIMO with Undefined Operation Points. Athenea Engineering Sciences Journal, 4(14), 8-21. https://doi.org/10.47460/athenea.v4i14.64
Abstract
This paper presents an algorithm for constructing fuzzy models in linear state subspaces from the nonlinear MIMO dynamic model of plants whose operating points are not defined within the permissible physical range for the system. It is based on the fuzzy Takagi-Sugeno-Kang model and Kawamoto's ideas of non-linearity sectors. The relevant functions in the antecedent are modeled with linear functions, while functions model the consequent in Discrete State Space. The application of the algorithm to the model of a thermoelectric plant widely studied in the specialized literature is discussed.
References
[1] A. Tewari, “Modern Control Design With MATLAB and SIMULINK”, Indian Institute of Technology, Kanpur, India, JOHN WILEY & SONS, LTD, ISBN 0 471 496790, pp. 323, 2002.
[2] J. Mendes, R. Araújo, y F. Souza, “Adaptive fuzzy identification and predictive control for industrial processes,” Expert Systems with Applications. Institute for Systems and Robotics (ISR-UC), and Department of Electrical and Computer Engineering (DEEC-UC), University of Coimbra, Portugal. pp. 2-15, November 2013.
[3] T. Takagi, y M. Sugeno, “Fuzzy Identification of Systems and Its Applications to Modeling and Control”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, VOL. SMC-15, NO. 1, pp. 116-132, JANUARY/FEBRUARY 1985.
[4] M. Sugeno y G. T. Kang, “STRUCTURE IDENTIFICATION OF FUZZY MODEL”, Fuzzy Sets and Systems 28 (1988), pp. 15-33, North-Holland.
[5] K. Mehran, “Takagi-Sugeno Fuzzy Modeling for Process Control”, Industrial Automation, Robotics and Arti¯cial Intelligence (EEE8005), Newcastle University, 2008.
[6] S. Kawamoto, K. Tada, A. Ishigame, and T. Taniguchi, “An approach to stability analysis of second order fuzzy systems", in Fuzzy Systems, 1992., IEEE International Conference on, pp. 1427-1434, 1992.
[7] R. Dimeo, K. Y. Lee, “Boiler-Turbine Control System Design Using a Genetic Algorithm”, IEEE Transactions on Energy Conversion, Vol. 10, No. 4, pp. 752-759, December 1995.
[8] R. A. Maher, I. A. Mohammed and I.K. Ibraheem, “State-Space Based H∞ Robust Controller Design for Boiler-Turbine System”, Arabian Journal for Science and Engineering, ISSN 1319-8025, April 2012.
[9] J. Novak, P. Chalupa, “Predictive Control of a Boiler-turbine System”, Recent Researches in Circuits and Systems, ISBN: 978-1-61804-108-1, pp. 383-388. 2012.
[10] J. Wu, J. Shen, M. Krug, S. K. NGUANG and Y. Li, “GA-based nonlinear predictive switching control for a boiler-turbine system”, Journal Control Theory Appl, pp. 100-106. 2012.
[11] A. H. Mazinan, “An Intelligent Multivariable Dynamic Matrix Control Scheme for a 160 MW Drum-type Boiler-Turbine System”, Journal of Electrical Engineering & Technology Vol. 7, No. 2, pp. 240-245, 2012.
[12] R. D. Bell and K. J. Aström, “Dynamic Models for Boiler-Turbine-Alternator Units: Data Logs and Parameter Estimation for a 160 MW Unit”, Deparment of Automatic Control, Lund Institute of Technology. Sweden, December 1987.
[13] J. Castillo, S. Sarmiento, A. Sanz, “ALGORITMO DE IDENTIFICACIÓN DIFUSA PARA EL MODELADO DE UN TANQUE CALENTADO POR SERPENTIN CON AGITACION CONTINUA”, Fifth LACCEI International Latin American and Caribbean Conference for Engineering and Technology (LACCEI’2007), 29 May – 1 June 2007, Tampico, México.
[2] J. Mendes, R. Araújo, y F. Souza, “Adaptive fuzzy identification and predictive control for industrial processes,” Expert Systems with Applications. Institute for Systems and Robotics (ISR-UC), and Department of Electrical and Computer Engineering (DEEC-UC), University of Coimbra, Portugal. pp. 2-15, November 2013.
[3] T. Takagi, y M. Sugeno, “Fuzzy Identification of Systems and Its Applications to Modeling and Control”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, VOL. SMC-15, NO. 1, pp. 116-132, JANUARY/FEBRUARY 1985.
[4] M. Sugeno y G. T. Kang, “STRUCTURE IDENTIFICATION OF FUZZY MODEL”, Fuzzy Sets and Systems 28 (1988), pp. 15-33, North-Holland.
[5] K. Mehran, “Takagi-Sugeno Fuzzy Modeling for Process Control”, Industrial Automation, Robotics and Arti¯cial Intelligence (EEE8005), Newcastle University, 2008.
[6] S. Kawamoto, K. Tada, A. Ishigame, and T. Taniguchi, “An approach to stability analysis of second order fuzzy systems", in Fuzzy Systems, 1992., IEEE International Conference on, pp. 1427-1434, 1992.
[7] R. Dimeo, K. Y. Lee, “Boiler-Turbine Control System Design Using a Genetic Algorithm”, IEEE Transactions on Energy Conversion, Vol. 10, No. 4, pp. 752-759, December 1995.
[8] R. A. Maher, I. A. Mohammed and I.K. Ibraheem, “State-Space Based H∞ Robust Controller Design for Boiler-Turbine System”, Arabian Journal for Science and Engineering, ISSN 1319-8025, April 2012.
[9] J. Novak, P. Chalupa, “Predictive Control of a Boiler-turbine System”, Recent Researches in Circuits and Systems, ISBN: 978-1-61804-108-1, pp. 383-388. 2012.
[10] J. Wu, J. Shen, M. Krug, S. K. NGUANG and Y. Li, “GA-based nonlinear predictive switching control for a boiler-turbine system”, Journal Control Theory Appl, pp. 100-106. 2012.
[11] A. H. Mazinan, “An Intelligent Multivariable Dynamic Matrix Control Scheme for a 160 MW Drum-type Boiler-Turbine System”, Journal of Electrical Engineering & Technology Vol. 7, No. 2, pp. 240-245, 2012.
[12] R. D. Bell and K. J. Aström, “Dynamic Models for Boiler-Turbine-Alternator Units: Data Logs and Parameter Estimation for a 160 MW Unit”, Deparment of Automatic Control, Lund Institute of Technology. Sweden, December 1987.
[13] J. Castillo, S. Sarmiento, A. Sanz, “ALGORITMO DE IDENTIFICACIÓN DIFUSA PARA EL MODELADO DE UN TANQUE CALENTADO POR SERPENTIN CON AGITACION CONTINUA”, Fifth LACCEI International Latin American and Caribbean Conference for Engineering and Technology (LACCEI’2007), 29 May – 1 June 2007, Tampico, México.
This work is licensed under a Creative Commons Attribution 4.0 International License.
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