Evolutionary design of Takagi-Sugeno fuzzy systems: a modular and hierarchical approach

Improves some results associated with a modular and hierarchical evolutionary design of fuzzy systems, using a Takagi-Sugeno approach. Basically, the set of design parameters to be adjusted is divided into modules distributed over different levels that evolve in an interactive way. Due to the existence of a compromise between the flexibility of the fuzzy system architecture and the efficiency of the evolutionary process, a significant gain in performance can be obtained when the set of parameters to be automatically defined is divided into two groups: one optimized using a least square procedure, and the other evolved using genetic algorithms. Simulation results show that the proposed method increases computational tractability and favor the descriptive nature of the final solution.