On the design and gain analysis of IT2-FLC with a case study on an electric vehicle

In this paper, we will present the gain analysis of an Internal Type-2 (IT2) Fuzzy Logic Controller (FLC) that employs the Nie-Tan method and validated our theoretical results on the control of realistic Electric Vehicle (EV) model. In this context, we will firstly present the analytical derivation of the employed IT2-FLC structure and its output in closed form. We will then investigate the gain variations with respect to the Footprint of Uncertainty (FOU) design parameter of the IT2-FLC. We will define aggressive and smooth control regions based on the gain of IT2 FLCs in comparison with its type-1 counterpart. We will also present the FOU parameter settings that obtain aggressive or smooth control actions based on derived controller gains. We will extend these gain analysis into controller design to achieve desired control action. We will present the simulation studies in which aggressive and smooth IT2-FLCs are compared and evaluated on the EV model for different control performance measures. The results will show that the presented gain analysis provides better understanding about the effect of the FOU parameter and an initiative way to tune IT2-FLC for control system applications.