The development and implementation of two multivariable nonlinear fuzzy modelbased adaptive predictive control schemes to a copolymerization process is described in this paper. Multi-input/single-output models are developed using fuzzy logic and combined to form a parallel system model for simulation and on-line prediction. The behavior of the outlined controllers were compared to the dynamic matrix control (DMC) and to a typical nonlinear model-based predictive control (typical NMPC) for regulatory problem. The obtained results showed the effectiveness of the proposed structures. © 2011 Elsevier B.V.29 694697Congalidis, J.P., Richards, J.R., Ray, W.H., Feedforward and feedback control of a solution copolymerization reactor (1989) AIChE Journal, 35 (6), pp. 891-907Dougherty, D., Cooper, D., A practical multiple model adaptive strategy for multivariable model predictive control (2003) Control Engineering Practice, 11, pp. 649-664Lima, N.M.N., Zuñiga Liñan, L., Maciel Filho, R., Embiruçu, M., Wolf Maciel, M.R., Grácio, F., Modeling and predictive control using fuzzy logic: application for a polymerization system (2010) AIChE Journal, 56 (4), pp. 965-978Lima, N.M.N., Manenti, F., Maciel Filho, R., Embiruçu, M., Wolf Maciel, M.R., Fuzzy model-based predictive hybrid control of polymerization processes (2009) Industrial & Engineering Chemistry Research, 48 (18), pp. 8542-8550Lima, N.M.N., Maciel Filho, R., Embiruçu, M., Wolf Maciel, M.R., A cognitive approach to develop dynamic models: application to polymerization systems (2007) Journal of Applied Polymer Science, 106, pp. 981-992Manenti, F., Dones, I., Buzzi-Ferraris, G., Preisig, H.A., Efficient numerical solver for partially structured DAE systems (2009) Industrial & Engineering Chemistry Research, 48 (22), pp. 9979-9984Takagi, T., Sugeno, M., Fuzzy identification of systems and its applications to modeling and control (1985) IEEE Transactions on Systems Man. and Cybernetics, 15 (1), pp. 116-133