Top-down approach for a linguistic fuzzy logic model

A top-down approach is introduced for processing nonlinear linguistic fuzzy logic within the Mamdani model itself in order to reduce the computational efforts. The top-down approach is composed of three steps: (1) directly obtain the best set of linguistic terms, (2) find the matching rule antecedents and their output values, and (3) visit the neighbor terms. A numerical example is provided along with detailed analysis of the approach. In addition, the approach is applied to a simplified aircraft conflict detection task. The results show that the top-down approach is effective at reducing the amount of computation compared to the classical search approach.