Automatic Generation of Hybrid Fuzzy/Numerical Controllers

In this paper, an automatic methodology for the generation 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 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. As a case study, we apply our methodology to the time optimal control of a dc motor. The results show that the hybrid controller outperforms both the numerical and the fuzzy ones.