Robust sampled-data model predictive control for networked systems with time-varying delay

In this paper, the problem of sampled-data model predictive control (MPC) is investigated for linear networked control systems with both input delay and input saturation. The delay-induced nonlinearity is overapproximatively modeled as a polytopic inclusion. The nonlinear behavior of input saturation is expressed as a convex polytope. The resulting closed-loop systems are represented as linear systems with polytopic and additive norm-bounded uncertainties. The aim is to determine a robust MPC controller that asymptotically stabilizes the uncertain system at the origin with a certain level of quadratic performance. The effectiveness of the proposed algorithm is demonstrated by a numerical example.