Details Details PDF BIBTEX RIS Title Neuro-fuzzy control design of processes in chemical technologies Journal title Archives of Control Sciences Yearbook 2012 Numer No 2 Authors Blahová, Lenka ; Dvoran, Ján ; Kmeťová, Jana Divisions of PAS Nauki Techniczne Publisher Committee of Automatic Control and Robotics PAS Date 2012 Identifier DOI: 10.2478/v10170-011-0022-2 ; ISSN 1230-2384 References Armfield. Instruction manual PCT40, 4th edition, 2005. ; Armfield. Instruction manual PCT41, 3rd edition, 2006. ; Armfield. Instruction manual PCT42, 2nd edition, 2006. ; Åstroöm K. (1989), Adaptive Control. ; Babuška R. (2003), Neuro-fuzzy methods for nonlinear system identification, Annual Reviews in Control, 73, doi.org/10.1016/S1367-5788(03)00009-9 ; Ová M. (2009), Robust stabilization of a chemical reactor, Chemical Papers, 5, 63, 527. ; Bastin G. (1990), On-line estimation and adaptive control of bioreactors. ; Blahová L. (2010), In Latest Trends on Systems, 14, 336. ; Chu J. (2003), An experimental study of model predictive control based on artificial neural networks, null, 1296. ; J. Dennis, JR. (1983), Numerical Methods for Unconstrained Optimization and Nonlinear Equations. ; Dostal P. (2007), Adaptive control of a continuous stirred tank reactor by two feedback controllers, null. ; Henson M. (1997), Nonlinear process control. ; Jang J. (1993), Adaptive-network-based fuzzy inference system, IEEE Trans. on Systems, Man, and Cybernetics, 23, 665, doi.org/10.1109/21.256541 ; Kvasnica M. (2010), Model predictive control of a CSTR: A hybrid modeling approach, Chemical papers, 3, 64, 301, doi.org/10.2478/s11696-010-0008-8 ; Liu S. (2002), Robust control based on neuro-fuzzy systems for a continuous stirred tank reactor, null. ; Maciejowski J. (2001), Predictive Control with Constraints. ; Marquardt D. (1963), An algorithm for least squares estimation of nonlinear parameters, J. of Society for Industrial and Applied Mathematics, 11, 431, doi.org/10.1137/0111030 ; Mészáros A. (2009), Intelligent control of a pH process, Chemical Papers, 2, 63, 180, doi.org/10.2478/s11696-009-0005-y ; Mikleš J. (2007), Process Modeling, Identification, and Control. ; Morari M. (1989), Robust Process Control. ; Sámek D. (2008), Semi-batch reactor predictive control using artificial neural network, null, 1532. ; Takagi T. (1985), Fuzzy identification of fuzzy systems and its applications to modeling and control, IEEE Trans. Systems, Man and Cybernetics, 15, 116, doi.org/10.1109/TSMC.1985.6313399 ; The Mathworks: Neural Network Toolbox, User's Guide, 2002.