Abstract

In most existing studies, scheduling parameters are assumed to be known and constant, which limits their applicability in practical applications. In this study, a new gain-scheduled feedback control system that addresses unknown and time-varying uncertainties is designed. These uncertainties are modeled using Sugeno-based type-3 fuzzy systems, where their upper and lower bounds are represented by type-3 fuzzy numbers rather than fixed constants. The scheduling parameters are estimated online using suggested adaptation laws derived by minimizing a cost function. Based on the estimated Sugeno-based type-3 fuzzy systems, a robust state-feedback law is designed, with sufficient stability conditions established using the Lyapunov approach. The proposed system is validated on various systems with non-identical dynamics, including a roll channel controller for an air-to-ground interceptor, an inverted pendulum, and a chaotic financial system with unknown dynamics. The results demonstrate the feasibility and good response of the designed scheme.

Keywords: Parameter-varying systems, Financial chaotic system, Uncertainties, Gain-scheduling, Type-3 (T3) fuzzy system, Linear matrix inequalities

Link: https://doi.org/10.5391/IJFIS.2025.25.4.389