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Design of a multivariable neural controller for control of a nonlinear MIMO plant

International Journal of Applied Mathematics and Computer Science's Cover Image
International Journal of Applied Mathematics and Computer Science
Signals and Systems (special section, pp. 233-312), Ryszard Makowski and Jan Zarzycki (Eds.)

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Akesson, B. and Tojvonen, H. (2006). A neural network model predictive controller, Journal of Process Control16(9): 937–946.10.1016/j.jprocont.2006.06.001Search in Google Scholar

Åström, K. and Wittenmark, B. (1995). Adaptive Control, Addison Weseley, Reading.Search in Google Scholar

Bańka, S. (2007). Multivariable Control Systems: A Polynomial Approach, Monographs of the Committee of Automation and Robotics, Polish Academy of Sciences, Szczecin University of Technology Press, Szczecin, (in Polish).Search in Google Scholar

Bańka, S. (2012). On methods of modal controller synthesis in MIMO systems, in K. Malinowski and M. Busłowicz (Eds.), Advances in Control Theory and Automation, Printing House of Białystok University of Technology, Białystok, pp. 35–46.Search in Google Scholar

Bańka, S., Dworak, P. and Brasel, M. (2010a). On control of nonlinear dynamic MIMO plants using a switchable structure of linear modal controllers, Pomiary, Automatyka, Kontrola56(5): 385–391, (in Polish).Search in Google Scholar

Bańka, S., Dworak, P., Brasel, M. and Latawiec, K.J. (2010b). A switched structure of linear MIMO controllers for positioning of a drillship on a sea surface, Proceedings of the 15th International Conference on Methods and Models in Automation and Robotics, MMAR 2010, Mi˛edzyzdroje, Poland, pp. 249–254.10.1109/MMAR.2010.5587228Search in Google Scholar

Bańka, S., Dworak, P. and Jaroszewski, K. (2011). Problems associated with realization of neural modal controllers designed to control multivariable dynamic systems, in K. Malinowski and R. Dindorf (Eds.), Advances of Automatics and Robotics, Kielce University of Technology Press, Kielce, pp. 27–41, (in Polish).Search in Google Scholar

Bańka, S., Dworak, P. and Jaroszewski, K. (2013). Linear adaptive structure for control of a nonlinear MIMO dynamic plant, International Journal of Applied Mathematics and Computer Science23(1): 47–63, DOI: 10.2478/amcs-2013-0005.10.2478/amcs-2013-0005Search in Google Scholar

Bańka S. and Latawiec, K.J. (2009). On steady-state error-free regulation of right-invertible LTI MIMO plants, Proceedings of the 14th International Conference on Methods and Models in Automation and Robotics, MMAR 2009, Mi˛edzyzdroje, Poland, DOI: 10.3182/20090819-3-PL-3002.00066.10.3182/20090819-3-PL-3002.00066Search in Google Scholar

Chen, J. and Yea, Y. (2002). Neural network-based predictive control for multivariable processes, Chemical Engineering Communications189(7): 865–894.10.1080/00986440213128Search in Google Scholar

Fabri, S. and Kadrikamanathan, V. (2001). Functional Adaptive Control. An Intelligent Systems Approach, Springer-Verlag, Berlin.10.1007/978-1-4471-0319-6Search in Google Scholar

Khalil, H.K. (2001). Nonlinear Systems, Prentice Hall, Englewood Cliffs, NJ.Search in Google Scholar

Ławryńczuk, M. (2010). Explicit neural network-based nonlinear predictive control with low computational complexity, in M. Szczuka, M. Kryszkiewicz, S. Ramanna, R. Jensen and Q. Hu (Eds.), Rough Sets and Current Trends in Computing, Lecture Notes in Computer Science, Vol. 6086, Springer, Berlin/Heidelberg, pp. 649–658.10.1007/978-3-642-13529-3_69Search in Google Scholar

Lee, C., Shin, M. and Chung, M. (2001). A design of gain-scheduled control for a linear parameter varying system: An application to flight control, Control Engineering Practice9(1): 11–21.10.1016/S0967-0661(00)00090-3Search in Google Scholar

Limon, D., Alamo, T. and Camacho, E. (2005). Enlarging the domain of attraction of MPC controllers, Automatica41(4): 629–635.10.1016/j.automatica.2004.10.011Search in Google Scholar

Maciejowski, J. (2002). Predictive Control with Constraints, Prentice Hall, Englewood Cliffs, NJ.Search in Google Scholar

Pedro, J.O. and Dahunsi, O.A. (2011). Neural network based feedback linearization control of a servo-hydraulic vehicle suspension system, International Journal of Applied Mathematics and Computer Science21(1): 137–147, DOI: 10.2478/v10006-011-0010-5.10.2478/v10006-011-0010-5Search in Google Scholar

Qin, S. and Badgwell, T. (2003). A survey of industrial model predictive control technology, Control Engineering Practice11(7): 733–764.10.1016/S0967-0661(02)00186-7Search in Google Scholar

Rawlings, J. and Mayne, D. (2009). Model Predictive Control: Theory and Design, Nob Hill Publishing, Madison, WI.Search in Google Scholar

Shevitz, D. and Paden, B. (1994). Lyapunov stability theory of nonsmooth systems, IEEE Transactions on Automatic Control39(9): 1910–1914.10.1109/9.317122Search in Google Scholar

Tatjewski, P. (2007). Advanced Control of Industrial Processes, Springer-Verlag, London.Search in Google Scholar

Tomera, M. (2010). Nonlinear controller design of a ship autopilot, International Journal of Applied Mathematics and Computer Science20(2): 271–280, DOI: 10.2478/v10006-010-0020-8.10.2478/v10006-010-0020-8Search in Google Scholar

Tzirkel-Hancock, E. and Fallside, F. (1992). Stable control of nonlinear systems using neural networks, International Journal of Robust and Nonlinear Control2(1): 63–86.10.1002/rnc.4590020105Search in Google Scholar

van der Boom, T., Botto, M. and Hoekstra, P. (2005). Design of an analytic constrained predictive controller using neural networks, International Journal of Systems Science36(10): 639–650.10.1080/00207720500150549Search in Google Scholar

Vidyasagar, M. (1985). Control System Synthesis: A Factorization Approach, MIT Press, Cambridge, MA.Search in Google Scholar

Wise, D.A. and English, J.W. (1975). Tank and wind tunnel tests for a drill-ship with dynamic position control, Offshore Technology Conference, Dallas, TX, USA, pp. 103–118.Search in Google Scholar

Witkowska, A., Tomera, M. and Smierzchalski, R. (2007). A backstepping approach to ship course control, International Journal of Applied Mathematics and Computer Science17(1): 73–85, DOI: 10.2478/v10006-007-0007-2.10.2478/v10006-007-0007-2Search in Google Scholar

Zhai, G. and Xu, X. (2010). A unified approach to stability analysis of switched linear descriptor systems under arbitrary switching, International Journal of Applied Mathematics and Computer Science20(2): 249–259, DOI: 10.2478/v10006-010-0018-2.10.2478/v10006-010-0018-2Search in Google Scholar

eISSN:
2083-8492
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Mathematics, Applied Mathematics