The paper proposes a methodology to self-evolve an online fuzzy logic controller (FLC). The proposed methodology does not require any initialization at all, it can start with an empty set of fuzzy control rules or with a simple collection of fuzzy control rules obtained from an expert operator. The FLC design is online, using only the input/output data obtained during the normal operation of the system while it is being controlled. The FLC is composed of a simple structure, where each input variable has its own set of fuzzy control rules, and is evaluated individually by the proposed methodology avoiding the high increase in the number of fuzzy control rules. The FLC structure and their antecedent and consequent parameters are both online modified by the proposed methodology. Only simple information about the system and controller is need, specifically the universe of discourse of the input and output variables, an information that is mandatory to control any process. The performance of the proposed methodology is tested on a simulated continuous-stirred tank reactor (CSTR) system where the results show that the proposed methodology has the capability of designing the FLC in order to successfully controlling the CSTR system by evolving/modifying the FLC structure when unknown regions of operation are reached (unknown for the controller).