Model Predictive Control for Nonlinear Systems Under Sample‐and‐Hold Control Structure: An Integral‐Type Double Self‐Triggering Method

Abstract

AbstractThis study examined the control problem of continuous‐time nonlinear systems under a sample‐and‐hold control structure. A new integral‐type double self‐triggered (ST) model predictive control (MPC) approach is developed by combining a novel ST strategy with MPC, which significantly decreases the sampling frequency of the system, saving computation/communication resources. In contrast to the traditional ST strategy, two integral‐type self‐triggering mechanisms are designed based on the mode of the state and the integral of the difference between the optimal and actual states. In addition, the integral‐type double ST‐MPC algorithm is developed, and the feasibility and stability of the closed‐loop system are rigorously demonstrated. Finally, the effectiveness and superiority of the proposed algorithm are verified by comparing the simulation results with those of existing ST‐MPC methods.