Inverse optimal fixed-time direct fuzzy control for nonlinear switched systems

This article investigates the problem of inverse optimal fixed-time tracking for nonlinear switched systems. Given this, a control scheme is developed based on an adaptive direct fuzzy inverse optimal and fixed time. The proposed control strategy accomplishes optimal performance without solutions for the Hamiltonian function. On the other hand, this scheme designs inverse optimal controller and virtual controller without involving partial differential derivative terms, using a one-parameter learning mechanism so that the time difference of the Lyapunov function is non-positive. Two common Lyapunov function candidates are employed to demonstrate that the proposed control scheme stabilizes the switched system and the tracking error converges to a predefined region.