Interval type-2 fuzzy logic controllers for flocking behavior

Abstract

This paper presents a novel interval type-2 fuzzy logic control architecture for flocking system when the system has noisy sensor measurements. The traditional type-1 fuzzy logic controller (FLC) using precise fuzzy sets cannot fully model and handle the uncertainties of sensor data. However, type-2 FLC using type-2 fuzzy sets with a footprint of uncertainty (FOU) produce better performances under noisy environments. In this paper, therefore, we present a control architecture for flocking behavior that is based on interval type-2 FLC to implement the flocking behaviors of separation, obstacle avoidance, and velocity matching. The type-2 based control system could cope with the uncertainties of noisy sensor measurements and resulted in good performances that outperformed the type-1 FLC.