A novel model predictive control strategy in modified PLS framework

A data-driven model predictive control (MPC) in modified partial least squares (PLS) framework is proposed in this paper after a brief summary of MPC strategy in PLS framework. A theoretical comparison between data-driven MPC strategy in these two framework is presented, which demonstrates that MPC in modified PLS framework benefits in both computation complexity and robustness. The feature of modeling rapidly makes it possible to update the correlation model online. The reliability of the model is guaranteed by the model update strategy to a certain degree. Performance of the proposed control strategy is verified through simulations of a numerical example. It can be illuminated from the simulation that the proposed method performances well.