LAUSR

In this paper, the problem of event-triggered robust model predictive control (MPC) was examined for a class of Lipchitz nonlinear networked control systems (NCS) with network-induced delays and subject to external disturbances. An event-triggering scheme for a continuous-time NCS was proposed, which reduced the communication traffic and computational burden of the MPC algorithm simultaneously. In comparison with the existing event-triggered nonlinear MPC (NMPC) approaches, the controller in this paper was designed as a state feedback control law, which minimized a “worst-case” performance index over an infinite horizon subject to constraints on the control input. The controller and event generator parameters were developed as a convex optimization problem, encompassing some linear matrix inequalities (LMIs). Simulation results showed that the proposed event-triggering NMPC scheme preserved closed-loop performance while reducing the communication rate and the computational time.