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A method of designing a nonlinear predictive controller based on relational fuzzy model is presented. The fuzzy model is incorporated as a predictor in a nonlinear model - based predictive controller, using internal model control scheme to compensate disturbances and modeling errors. A non-convex optimization problem must be solved at each sampling period. The algorithm is applied to temperature control in a heat exchanger.