[Blevins, T., McMillan, G., Wojsznis, W. and Brown, M. (2003). Advanced Control Unleashed, ISA—The Instrumentation, Systems, and Automation Society, Research Triangle Park, NC.]Search in Google Scholar
[Camacho, E. and Bordons, C. (1999). Model Predictive Control, Springer-Verlag, London.10.1007/978-1-4471-3398-8]Search in Google Scholar
[Cao, S., Rees, N. and Feng, G. (1997). Analysis and design for a class of complex control systems. Part I: Fuzzy modelling and identification, Automatica 33(6): 1017-1028.]Search in Google Scholar
[Chen, J., Xi, Y. and Zhang, Z. (1998). A clustering algorithm for fuzzy model identification, Fuzzy Sets and Systems 98(3): 319-329.10.1016/S0165-0114(96)00384-3]Search in Google Scholar
[Cutler, C. and Ramaker, B. (1980). Dynamic matrix control—A computer control algorithm, Proceedings of the Joint Automatic Control Conference, San Francisco, CA, USA, paper no. WP5-B.]Search in Google Scholar
[Driankov, D., Hellendoorn, H. and Reinfrank, M. (1993). An Introduction to Fuzzy Control, Springer-Verlag, Berlin.10.1007/978-3-662-11131-4]Search in Google Scholar
[Garcia, C. (1984). Quadratic dynamic matrix control of nonlinear processes: An application to a batch reaction process, Proceedings of the AIChE Annual Meeting, San Francisco, CA, USA, paper no. 82f.]Search in Google Scholar
[Garcia, C. and Morshedi, A. (1986). Quadratic programming solution of dynamic matrix control (QDMC), Chemical Engineering Communications 46(1-3): 73-87.10.1080/00986448608911397]Search in Google Scholar
[Gattu, G. and Zafiriou, E. (1992). Nonlinear quadratic dynamic matrix control with state estimation, Industrial and Engineering Chemistry Research 31(4): 1096-1104.10.1021/ie00004a018]Search in Google Scholar
[Lee, J. and Ricker, N. (1994). Extended Kalman filter based nonlinear model predictive control, Industrial and Engineering Chemistry Research 33(6): 1530-1541.10.1021/ie00030a013]Search in Google Scholar
[Li, W. and Biegler, L. (1989). Multistep, Newton-type control strategies for constrained, nonlinear processes, Chemical Engineering Research and Design 67(Nov.): 562-577.]Search in Google Scholar
[Maciejowski, J. (2002). Predictive Control with Constraints, Prentice Hall, Harlow.]Search in Google Scholar
[Marusak, P. (2002). Predictive control of nonlinear plants using dynamic matrix and fuzzy modeling, Ph. D. thesis, Warsaw University of Technology, Warsaw, (in Polish).]Search in Google Scholar
[Marusak, P. and Tatjewski, P. (2000). Fuzzy dynamic matrix control algorithms for nonlinear plants, Proceedings of the 6-th International Conference on Methods and Models in Automation and Robotics MMAR 2000, Międzyzdroje, Poland, pp. 749-754.]Search in Google Scholar
[Marusak, P. and Tatjewski, P. (2001). Stability analysis of nonlinear control systems with fuzzy DMC controllers, Proceedings of the IFAC Workshop on Advanced Fuzzy and Neural Control, AFNC'01, Valencia, Spain, pp. 21-26.]Search in Google Scholar
[Marusak, P. and Tatjewski, P. (2002). Stability analysis of nonlinear control systems with unconstrained fuzzy predictive controllers, Archives of Control Sciences 12(3): 267-288.]Search in Google Scholar
[Marusak, P. and Tatjewski, P. (2003). Stable, effective fuzzy DMC algorithms with on-line quadratic optimization, Proceedings of the American Control Conference, ACC 2003, Denver, CO, USA, pp. 3513-3518.]Search in Google Scholar
[Mayne, D., Rawlings, J., Rao, C. and Scokaert, P. (2000). Constrained model predictive control: Stability and optimality, Automatica 36(6): 789-814.10.1016/S0005-1098(99)00214-9]Search in Google Scholar
[Michalska, H. and Mayne, D. (1993). Robust receding horizon control of constrained nonlinear systems, IEEE Transactions on Automatic Control 38(11): 1623-1632.10.1109/9.262032]Search in Google Scholar
[Morari, M. and Lee, J. (1999). Model predictive control: Past, present and future, Computers and Chemical Engineering 23(4): 667-682.10.1016/S0098-1354(98)00301-9]Search in Google Scholar
[Mutha, R., Cluett, W. and Penlidis, A. (1997). Nonlinear model-based predictive control of control nonaffine systems, Automatica 33(5): 907-913.10.1016/S0005-1098(96)00220-8]Search in Google Scholar
[Mutha, R., Cluett, W. and Penlidis, A. (1998). Modifying the prediction equation for nonlinear model-based predictive control, Automatica 34(10): 1283-1287.10.1016/S0005-1098(98)00082-X]Search in Google Scholar
[Piegat, A. (2001). Fuzzy Modeling and Control, Physica-Verlag, Berlin.10.1007/978-3-7908-1824-6]Search in Google Scholar
[Rossiter, J. (2003). Model-Based Predictive Control, CRC Press, Boca Raton, FL.]Search in Google Scholar
[Scokaert, P., Mayne, D. and Rawlings, J. (1999). Suboptimal model predictive control (feasibility implies stability), IEEE Transactions on Automatic Control 44(3): 648-654.10.1109/9.751369]Search in Google Scholar
[Setnes, M. and Roubos, H. (2000). GA-fuzzy modeling and classification: Complexity and performance, IEEE Transactions on Fuzzy Systems 8(5): 509-522.10.1109/91.873575]Search in Google Scholar
[Takagi, T. and Sugeno, M. (1985). Fuzzy identification of systems and its application to modeling and control, IEEE Transactions on Systems, Man and Cybernetics 15(1): 116-132.10.1109/TSMC.1985.6313399]Search in Google Scholar
[Tanaka, K. and Sugeno, M. (1992). Stability analysis and design of fuzzy control systems, Fuzzy Sets and Systems 45(2): 135-156.10.1016/0165-0114(92)90113-I]Search in Google Scholar
[Tatjewski, P. (2007). Advanced Control of Industrial Processes; Structures and Algorithms, Springer-Verlag, London.]Search in Google Scholar
[Yager, R. and Filev, D. (1994). Essentials of Fuzzy Modeling and Control, Wiley, New York, NY.]Search in Google Scholar