Open Access
Issue |
E3S Web Conf.
Volume 124, 2019
International Scientific and Technical Conference Smart Energy Systems 2019 (SES-2019)
|
|
---|---|---|
Article Number | 05031 | |
Number of page(s) | 4 | |
Section | Additional papers | |
DOI | https://doi.org/10.1051/e3sconf/201912405031 | |
Published online | 10 February 2020 |
- W.S. McCulloch, W. Pitts, A logical calculus of ideas imminent in nervous activity Bull. Math. Biophys, 5, 115–133 (1943) [Google Scholar]
- M. Saerens, A. Soquet, Neural controller based on back-propagation algorithm, IEE Proc. F Radar and Signal Processing, 138, 55–62 (1991) [CrossRef] [Google Scholar]
- J. Hopfield, D. Tank, Neural computation of decisions optimization problems, Biological Cybernetics, 52, 141–152 (1985) [PubMed] [Google Scholar]
- G. Carpenter, S. Grossberg, The ART of adaptive pattern recognition by a self-organizing neural network, IEEE Computer, 21, 77–88 (1988) [CrossRef] [Google Scholar]
- A. Michel, J. Farrell, Associative memories via artificial neural networks, IEEE Control Systems Magazine, 10, 6–17 (1990) [CrossRef] [Google Scholar]
- K.J. Hunt, D. Sbarbaro, R. Żbikowski, P.J. Gawthrop, Neural networks for control systems: a survey Automatica, Journal of IFAC, 28, 1083–112 (1992) [Google Scholar]
- K.S. Narendra, K. Parthasarathy, Identification and control of dynamical systems using neural networks, IEEE Trans Neural Networks, 1, 4–27 (1990) [Google Scholar]
- D.E. Rumelhart, G.E. Hinton, R.J. Williams, Learning internal representation by error propagation, Parallel distributed processing: explorations in the microstructure of cognition, 1, 318–362 (1986) [Google Scholar]
- A. Kayashev, E. Muravyova, M. Sharipov, A. Emekeev, A. Sagdatullin, Verbally defined processes controlled by fuzzy controllers with input/output parameters represented by set of precise terms, Proceedings of 2014 International Conference on Mechanical Engineering, Automation and Control Systems, MEACS 2014, 6986847 (2014) [Google Scholar]
- M. Minsky, S. Papert, Perceptrons, Expanded Edition: An introduction to computational geometry, 308 (1988) [Google Scholar]
- P. Vas, Vector control of AC machines (1990) [Google Scholar]
- A.U. Levin, K.S. Narendra, Control of nonlinear dynamical systems using neural networks: controllability and stabilization, IEEE Transactions on Neural Networks, 4, 192–206 (1993) [CrossRef] [PubMed] [Google Scholar]
- D.H. Nguyen, B. Widrow, Neural networks for selflearning control systems, IEEE Control Systems Magazine, 10, 18–23 (1991) [CrossRef] [Google Scholar]
- A.V. Basharin, V.A. Novikov, G.G. Sokolovskiy, Control of electrical drives: Textbook for higher educational institution, 392 (1982) [Google Scholar]
- R.A. Marchi, F.J. Von Zuben, E. Bim, A neural network approach for the direct power control of a doubly fed induction generator, XI Brazilian Power Electronics Conference (2011) [Google Scholar]
- S. Haykin, Neural Networks and Learning Machines, 906 (2009) [Google Scholar]
- A.M. Sagdatullin, Development and Modeling of Automation and Control System of Sucker-Rod Well Pump with Beam Drive (2016) https://doi.org/10.1007/s10556-016-0142-4 [Google Scholar]
- Y. Djeriri, A. Meroufel, M. Allam, Artificial neural network-based robust tracking control for doubly fed induction generator used in wind energy conversion systems, Journal of Advanced Research in Science and Technology, 2, 173–181 (2015) [Google Scholar]
- P.J. Werbos, Neural networks, system identification, and control in the chemical process industries, Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches, 10(A), 283–356 (2015) [Google Scholar]
- J.A. Leonard, M.A. Kramer, Classifying process behaviour with neural networks:strategies for improved training and generalization, American Control Conference, 3, 2478–83 (1990) [Google Scholar]
- L. Ljung, T. Söderström, Theory and practice of recursive identification, 501 (1985) [Google Scholar]
- P.A. Lant, M.J. Willis, G.A. Montague, M.T. Tham, A.J. Morris, A comparison of adaptive estimation with neural based techniques for bioprocess application, Proceedings of the American Control Conference, 21, 2173–78 (1990) [Google Scholar]
- M. Willis, D.C. Massimo, G. Montague, M. Tham, J. Morris, Artificial neural networks in process engineering, Control Theory and Applications, IEE Proceedings, 138, 256–266 (1991) [CrossRef] [Google Scholar]
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