A Comparison of Non-stationary, Type-2 and Dual Surface Fuzzy Control
This work addresses control system robustness under uncertainty for applications like autonomous sailing, but it is incremental as it compares existing fuzzy methods without introducing a new paradigm.
The paper compared type-1 fuzzy control with interval type-2, non-stationary, and dual surface type-2 controllers in a simulated autonomous sailing problem under environmental uncertainty, finding that more sophisticated controllers can outperform type-1 but performance depends heavily on the Footprint of Uncertainty size.
Type-1 fuzzy logic has frequently been used in control systems. However this method is sometimes shown to be too restrictive and unable to adapt in the presence of uncertainty. In this paper we compare type-1 fuzzy control with several other fuzzy approaches under a range of uncertain conditions. Interval type-2 and non-stationary fuzzy controllers are compared, along with 'dual surface' type-2 control, named due to utilising both the lower and upper values produced from standard interval type-2 systems. We tune a type-1 controller, then derive the membership functions and footprints of uncertainty from the type-1 system and evaluate them using a simulated autonomous sailing problem with varying amounts of environmental uncertainty. We show that while these more sophisticated controllers can produce better performance than the type-1 controller, this is not guaranteed and that selection of Footprint of Uncertainty (FOU) size has a large effect on this relative performance.