Robust MPC for LPV systems via a novel optimization-based constraint tightening

We propose a novel approach to design robust Model Predictive Controller (MPC) for constrained uncertain linear systems. The system is modeled as parameter varying with an additive disturbance. Set bounds the matrices and uncertainty are assumed be known. formulate optimization-based constraint tightening strategy around predicted nominal trajectory which utilizes these bounds. With appropriately designed terminal cost function set, we prove satisfaction of imposed constraints by resulting MPC in closed-loop system, Input State Stability origin. highlight efficacy our proposed via numerical example.