With the development of predictive control technology

more and more researches tend to reduce the computational and data transmission burden of controllers. This paper proposes a model predictive control method based on an event-triggered mechanism for controlling continuous time nonlinear mobile robot systems. Specifically

two different event-triggered strategies are constructed at the sensor node and controller node to reduce communication and computational load

and a dual-mode control strategy is adopted to reduce computational pressure further while ensuring system stability. In addition

a robust constraint is designed to handle external additive disturbance faced by the system

and sufficient conditions are theoretically provided to ensure closed-loop stability of the system under aperiodic triggering. Finally

the feasibility and effectiveness of the proposed method were verified through simulation experiments of a wheeled robot system.