Reliable Model Predictive Control for Linear Sampled-Data System with Input Constraints

In this paper, a novel model predective control algorithm is proposed. By discretizing the sampled-data system and transforming it into a polytopic uncertain system, a reliable model predictive controller is designed for the sampled-data system. Based on this transfer, a class of linear matrix inequalities is formulated as the sampled-data controller. Finally, a simulation of numerical example is presented to verify the result.