An investigation into the relationship between type-2 FOU size and environmental uncertainty in robotic control

TL;DR

This study investigates how the size of type-2 fuzzy logic's footprint of uncertainty affects robotic control performance under environmental uncertainty, revealing that optimal FOU sizing can enhance or impair control effectiveness.

Contribution

It provides a detailed analysis of the impact of type-2 FOU size on control performance in uncertain environments, highlighting the importance of proper FOU sizing.

Findings

Type-2 fuzzy controllers can outperform type-1 under certain conditions.

Incorrect FOU sizing can lead to significant performance penalties.

Optimal FOU size depends on the level of environmental uncertainty.

Abstract

It has been suggested that, when faced with large amounts of uncertainty in situations of automated control, type-2 fuzzy logic based controllers will out-perform the simpler type-1 varieties due to the latter lacking the flexibility to adapt accordingly. This paper aims to investigate this problem in detail in order to analyse when a type-2 controller will improve upon type-1 performance. A robotic sailing boat is subjected to several experiments in which the uncertainty and difficulty of the sailing problem is increased in order to observe the effects on measured performance. Improved performance is observed but not in every case. The size of the FOU is shown to be have a large effect on performance with potentially severe performance penalties for incorrectly sized footprints.