The model predictive control (MPC) based ramp metering strategy was explored, in which online nonlinear optimization was applied.The dynamic nonlinear timediscrete optimal control model was established and the associated solving algorithm was presented.In the optimal control,a dynamic expressway network traffic flow model was adopted as the process model,and a genetic algorithm was applied to solve the optimization problem.By a simulated case study the efficiency and robustness of the MPC strategy was tested.The results show that,the MPC strategy can obviously alleviate congestion and improve the overall network performance.It can control vehicle flow more smoothly comparing to the widely used ALINEA feedback control strategy.The performance criterion of TTS (total time spent) is 1.2% higher,thus it is of good control robustness.