Aperiodic Sampled-Data $H_{\infty }$ Control of Vehicle Active Suspension System: An Uncertain Discrete-Time Model Approach

In this article, the matter of aperiodic sampled-data
$H_{\infty }$
control of a quarter vehicle active suspension system with time-varying delay is investigated based on an uncertain discrete-time model. This article mainly solves three problems based on the theory of integral quadratic constraints. First, the system is discretized by resorting to lifting technique, the uncertainties of the discrete-time model are embodied by the operators related to sampled-data and time delay, in this process, a new norm upper bound estimation of operator is given. Second, based on the multipliers of the operator, the conditions for the improved
$H_{\infty }$
performance constraints are given. Third, with regard to controller design, the difficulties posed by the nonlinear coupling terms for solving the matrix inequalities are addressed by an iterative algorithm. Finally, the simulation platform and a practical example show that the proposed method is effect and can obtain more optimized results.