Fuzzy adaptive finite-time inverse optimal control for active suspension systems

This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems (ASSs). The fuzzy logic systems (FLSs) are utilized to learn the unknown non-linear dynamics and an auxiliary system is established. Based on the finite-time stability theory and inverse optimal theory, a fuzzy adaptive inverse finite-time inverse optimal control method is proposed. It is proven that the formulated control approach guarantees the stability of the controlled systems, while ensuring that errors converge to a small neighborhood of zero within finite time. Moreover, the optimized control performance can be achieved. Eventually, the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.