Removing Feasibility Conditions on Adaptive Fuzzy Control of State-Constrained High-Order Nonlinear Systems

This paper investigates adaptive fuzzy control for full-state constrained high-order nonlinear systems. Fuzzy systems are employed to approximate unknown system nonlinearities. By integrating nonlinear transformed functions into control design, full-state constraints can be handled without imposing feasibility conditions on virtual controllers. It is rigorously proved that fuzzy approximation is valid on a crucial compact set, full-state constraints aren't violated for all time, and the tracking error converges to a small compact set around zero. A simulation example shows the effectiveness of this control scheme.