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Volumn 60, Issue 23, 2005, Pages 6718-6732

Dynamic recurrent radial basis function network model predictive control of unstable nonlinear processes

Author keywords

Automatic configuration; Model predictive control; Neural network; On line learning; Radial basis function network; Unstable nonlinear processes

Indexed keywords

CHEMICAL REACTORS; CONTROL EQUIPMENT; INDUSTRIAL PLANTS; LEARNING ALGORITHMS; NEURAL NETWORKS; NONLINEAR SYSTEMS; POLYMERIZATION; RADIAL BASIS FUNCTION NETWORKS; THREE TERM CONTROL SYSTEMS;

EID: 27444441175     PISSN: 00092509     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ces.2005.03.070     Document Type: Article
Times cited : (43)

References (20)
  • 1
    • 0021497175 scopus 로고
    • Automatic tuning of simple regulators with specifications on phase and amplitude margins
    • Astrom, K.J., Hagglund, T., 1984. Automatic tuning of simple regulators with specifications on phase and amplitude margins. Automatica 20, 645-651.
    • (1984) Automatica , vol.20 , pp. 645-651
    • Astrom, K.J.1    Hagglund, T.2
  • 3
    • 0035112326 scopus 로고    scopus 로고
    • Factorized approach to nonlinear MPC using a radial basis function model
    • Bhartiya, S., Whitely, J.R., 2001. Factorized approach to nonlinear MPC using a radial basis function model. American Institute of Chemical Engineers 47, 358-368.
    • (2001) American Institute of Chemical Engineers , vol.47 , pp. 358-368
    • Bhartiya, S.1    Whitely, J.R.2
  • 4
    • 0024090586 scopus 로고
    • Feedforward and feedback linearization of nonlinear systems and its implementation using internal model control (IMC)
    • Calvet, J.P., Arkun, Y., 1988. Feedforward and feedback linearization of nonlinear systems and its implementation using internal model control (IMC). Industrial and Engineering Chemistry Research 27, 1822-1831.
    • (1988) Industrial and Engineering Chemistry Research , vol.27 , pp. 1822-1831
    • Calvet, J.P.1    Arkun, Y.2
  • 6
    • 0024668467 scopus 로고
    • Model predictive control: Theory and practice - A survey
    • Garcia, C.E., Prett, D.M., Morari, M., 1989. Model predictive control: theory and practice - a survey. Automatica 25, 335-348.
    • (1989) Automatica , vol.25 , pp. 335-348
    • Garcia, C.E.1    Prett, D.M.2    Morari, M.3
  • 7
    • 0032455115 scopus 로고    scopus 로고
    • Nonlinear model predictive control: Current status and future directions
    • Henson, A., 1998. Nonlinear model predictive control: current status and future directions. Computers and Chemical Engineering 23, 187-202.
    • (1998) Computers and Chemical Engineering , vol.23 , pp. 187-202
    • Henson, A.1
  • 8
    • 0026849116 scopus 로고
    • Study of the control relevant properties of backpropagation neural network models of nonlinear dynamical systems
    • Hernandez, E., Arkun, Y., 1992. Study of the control relevant properties of backpropagation neural network models of nonlinear dynamical systems. Computers and Chemical Engineering 16, 227-240.
    • (1992) Computers and Chemical Engineering , vol.16 , pp. 227-240
    • Hernandez, E.1    Arkun, Y.2
  • 11
    • 0032735194 scopus 로고    scopus 로고
    • Review of the applications of neural networks in chemical process control-simulation and on-line implementation
    • Hussain, M.J., 1999. Review of the applications of neural networks in chemical process control-simulation and on-line implementation. Artificial Intelligence in Engineering 13, 55-68.
    • (1999) Artificial Intelligence in Engineering , vol.13 , pp. 55-68
    • Hussain, M.J.1
  • 12
    • 0029393368 scopus 로고
    • Neural model predictive control (NMPC) of a distributed parameter crystal growth process
    • Ishida, M., Zhan, J., 1995. Neural model predictive control (NMPC) of a distributed parameter crystal growth process. American Institute of Chemical Engineers 41, 2333-2336.
    • (1995) American Institute of Chemical Engineers , vol.41 , pp. 2333-2336
    • Ishida, M.1    Zhan, J.2
  • 13
    • 0025839504 scopus 로고
    • A Gaussian potential function network with hierarchically self-organizing learning
    • Lee, S., Kil, R.M., 1991. A Gaussian potential function network with hierarchically self-organizing learning. Neural Networks 4, 207-224.
    • (1991) Neural Networks , vol.4 , pp. 207-224
    • Lee, S.1    Kil, R.M.2
  • 14
    • 0031192256 scopus 로고    scopus 로고
    • Polymerization reactor control using autoregressive plus Volterra-based MPC
    • Maner, B.R., Doyle, F.J., 1997. Polymerization reactor control using autoregressive plus Volterra-based MPC. American Institute of Chemical Engineers 43, 1763-1784.
    • (1997) American Institute of Chemical Engineers , vol.43 , pp. 1763-1784
    • Maner, B.R.1    Doyle, F.J.2
  • 16
    • 0031152395 scopus 로고    scopus 로고
    • A nonlinear predictive control strategy based on radial basis function models
    • Pottman, M., Seborg, D.E., 1997. A nonlinear predictive control strategy based on radial basis function models. Computers and Chemical Engineering 21, 965-980.
    • (1997) Computers and Chemical Engineering , vol.21 , pp. 965-980
    • Pottman, M.1    Seborg, D.E.2
  • 18
    • 0027399830 scopus 로고
    • Neural model predictive control for nonlinear chemical processes
    • Song, J.J., Park, S., 1993. Neural model predictive control for nonlinear chemical processes. Journal of Chemical Engineering of Japan 26, 347-354.
    • (1993) Journal of Chemical Engineering of Japan , vol.26 , pp. 347-354
    • Song, J.J.1    Park, S.2
  • 19
    • 0016050013 scopus 로고
    • On the dynamic behavior of continuous stirred tank reactors
    • Uppal, A., Ray. W.H., Poore, A.B., 1974. On the dynamic behavior of continuous stirred tank reactors. Chemical Engineering Science 29, 967-985.
    • (1974) Chemical Engineering Science , vol.29 , pp. 967-985
    • Uppal, A.1    Ray, W.H.2    Poore, A.B.3
  • 20
    • 0030871526 scopus 로고    scopus 로고
    • The multi-step predictive control of nonlinear SISO processes with a neural model predictive control (NMPC) method
    • Zhan, J., Ishida, M., 1997. The multi-step predictive control of nonlinear SISO processes with a neural model predictive control (NMPC) method. Computers and Chemical Engineering 21, 201-210.
    • (1997) Computers and Chemical Engineering , vol.21 , pp. 201-210
    • Zhan, J.1    Ishida, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.