Abstract:This paper studies the path following problem of nonlinear unmanned vehicle models with bounded disturbances, and proposes an event-triggered model predictive control algorithm. Compared with the existing model predictive control algorithm based on time period, the proposed algorithm can guarantee the accuracy of following the reference trajectory of the vehicle and reduce the computational complexity of solving optimization problems in the following process, then it can reduce the computational burden of on-line real-time optimization. Finally, the simulation results of the unmanned vehicle kinematics model are given. Through the comparision with the traditional algorithm, the effectiveness of the proposed algorithm is verified.