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In this paper, a framework for the automatic synthesis of hybrid fuzzy/numerical controllers is proposed. The methodology is based on model checking and on a very precise analysis of a system. This allows one to synthesize optimal numerical controllers and then use them to consistently improve fuzzy controllers. Moreover, we present a new approach that integrates the numerical and the fuzzy components and automatically outputs a hybrid controller. Such a hybrid controller exploits the optimality of numerical controllers and the robustness of fuzzy ones, and it is very compact and fast to read thanks to the use of OBDDs. We apply our methodology to two benchmark problems, the dc motor and the inverted pendulum. The results show that the hybrid controller can handle linear as well as nonlinear systems outperforming both the numerical and the fuzzy controllers.