Sampled-Data L2-L∞ Filter-Based Fuzzy Control for Active Suspensions

In this paper, we present a new sampled-data
$\mathcal {L}_{2}-\mathcal {L}_{\infty }$
filter-based output feedback fuzzy control design technique for active suspension systems subjected to hard constraints. The sampled-data problem of continuous-time suspension systems is solved using an input delay approach. In this manner, the conservatism that occurs when designing filters and controllers is effectively alleviated by using Wirtinger’s inequality with the extended reciprocally convex combination bounding technique. We designed an
$\mathcal {L}_{2}-\mathcal {L}_{\infty }$
filter-based output-feedback fuzzy controller by using the Lyapunov–Krasovskii theorem to ensure that the closed-loop system is robust against external disturbances and sampled noise. The results of simulations involving different types of road disturbances and noise demonstrate the effectiveness of the proposed approach.