PREDICTIVE CONTROL OF CHAOTIC DISCRETE PLANTS

PREDICTIVE CONTROL OF CHAOTIC DISCRETE PLANTS

PREDICTIVE CONTROL OF CHAOTIC DISCRETE PLANTS

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  • Camacho, E.F. Model predictive control, Springer Verlag, 1998.
  • Garcia, C.E., Prett, D.M., and Morari, M. Model predictive control: theory and practice- a survey, Automatica, 25(3), pp.335-348, 1989.
  • Badgwell, A.B., Qin, S.J. Review of nonlinear model predictive control applications, In Nonlinear predictive control theory and practice, Kouvaritakis, B, Cannon, M (Eds.), IEE Control Series, pp.3-32, 2001.
  • Parker, R.S., Gatzke E.P., Mahadevan, R., Meadows, E.S., and Doyle, F.J. Nonlinear model predictive control: issues and applications, In Nonlinear predictive control theory and practice, Kouvaritakis, B, Cannon, M (Eds.), IEE Control Series, pp.34-57, 2001.
  • Babuska, R., Botto, M.A., Costa, J.S.D., and Verbruggen, H.B. Neural and fuzzy modeling on nonlinear predictive control, a comparison study, Computatioinal Engineering in Systems Science, July, 1996.
  • Nelles, O. Nonlinear system identification: from classical approach to neuro-fuzzy identification, Springer Verlag, 2001.
  • Narendra, K. S., and Parthasarathy, K., Identification and control of dynamic systems using neural networks. IEEE Transactions on Neural Networks, 1, pp.4–27, 1990.
  • Arahal, M.R., Berenguel, M., and Camacho, E.F. Neural identification applied to predictive control of a solar plant, Con. Eng. Prac. 6(3), pp.333-344, 1998.
  • Lennox, B., and Montague, G. Neural network control of a gasoline engine with rapid sampling, In Nonlinear predictive control theory and practice, Kouvaritakis, B, Cannon, M (Eds.), IEE Control Series, pp.245-255, 2001.
  • Petrovic, I., Rac, Z., and Peric, N. Neural network based predictive control of electrical drives with elastic transmission and backlash, Proc. EPE2001, Graz, Austria, 2001.
  • Tan, Y. and Cauwenberghe, A. Non-linear one step ahead control using neural networks: control strategy and stability design, Automatica (12), pp.1701-1706, 1996.
  • Temeng, H., Schenelle, P. and McAvoy, T. Model predictive control of an industrial packed bed reactor using neural networks, J. Proc. Control 5(1), pp.19-28, 1995.
  • Zamarrano, J.M., Vega, P. Neural predictive control. Application to a highly nonlinear system, Engineering Application of Artificial Intelligence, 12(2), pp.149-158, 1999.
  • Draeger, A., Engel, S., and Ranke, H., Model predictive control using neural networks, IEEE Control System Magazine, 15, pp.61–66, Gomm, J. B., Evans, J. T., and Williams, D., Development and performance of a neural network predictive controller. Control Engineering Practice, 5(1), pp.49–60, 1997.
  • Diyaz, G., Sen, M., Yang, K.T., McClain, R.L., Simulation of heat exchanger performance by artificial neural networks, Int. J. HVAC and R Res., 5 (3), pp.195-208, 1999.
  • Ayoubi, M., Dynamic multi-layer perception networks: application to the nonlinear identification and predictive control of a heat exchanger, in: Applications of Neural Adaptive Control Technology, World Scientific series in Robotics and Intelligent Systems, 17, pp.205- , 1997.
  • Renotie, C., Wouwer, A.V. and Remy, M. Neural modeling and control of a heat exchanger based on SPSA techniques, Proc. American Control Conference, Illinois, pp.3299-3303,
  • Bittanti, S. and Piroddi, L. Nonlinear identification and control of a heat exchanger: a neural network approach, Journal of the Franklin Institute, 1996.
  • Lim, K.W. and Ling, K.V. generalized predictive control of a heat exchanger, IEEE Control System Magazine, pp.9-12, 1989.
  • Parte, M.P. and Camacho, E.F. Application of a predictive sliding mode controller to a heat exchanger, Application, Glasgow, Scotland, pp.1219-1224,
  • Montague, G.A., Willis, M.J., Tham, M.T., Morris, A.J., (1991). Artificial neural network based control. International Conference on Control, pp.266–271.
  • Skrijave, I. and Matko, D. Predictive functional control based on fuzzy model for heat exchanger pilot plant, IEEE Trans. Fuzzy Systems, 8(6), pp.705-812, 2000.
  • Nelles, O. and R. Isermann (1996). Basis function networks for interpolation of local linear models. In: IEEE Conference on Decision and Control (CDC). Kobe, Japan. pp. 470–475.
  • Liu, G.P., 2001, Nonlinear Identification and Control: A Neural Network Approach, Springer.
  • Hunt, K.J., Sbarbaro, D., Zbikowski, R., Gawthrop, P.J., (1992). Neural networks for control system—A survey. Automatica, 28, pp.1083–1112.
  • Takahashi, Y., (1993). Adaptive predictive control of nonlinear time varying system using neural network, in Proc. IEEE International
  • Symposium on Neural Networks, pp.1464–1468.
  • Chen, G. and Moiola, J. L. An overview of bifurcation, chaos, and nonlinear dynamics in nonlinear system, J. Franklin Inst., vol. 331B, pp. 858, 1994.
  • Ogorzalek, M. J. Taming chaos, Part two: control, IEEE Trans. Circuits Syst. I, vol. 40, pp. 706, 1993.
  • Chen, G. and Done, X. From chaos to order: methodologies, perspectives and applications, World Scientific, Singapore, 1998.
  • Fradkov, A. L. and Pogromsky, A. Y. Introduction to control of oscillations and chaos, World Scientific, Singapore, 1998.