Model Predictive Control Using Dual Prediction Horizons for Lateral Control

In this paper, we present model predictive control having dual prediction horizons to reduce the length of prediction horizon and obtain the optimal solution rapidly. If prediction horizon is long, it is easy to get optimal solution while assuring closed-loop system stability. Realtime solution is, however, very difficult to calculate within the sample time because the system has complex formulations involving many constraints. On other hand, if prediction horizon is very short, computation overhead is reduced but the stability and performance of closed-loop system are not guaranteed. In this paper, the proposed method reduces the length of prediction horizon as well as maintains the stability and performance. The comparison of performances between the conventional method and the proposed control method are validated via simulations.