A robust MPC design for hot rolling mills: a polyhedral invariant sets approach

The role of a hot rolling mill process is to produce strips of thickness about 0.8 ~ 20 mm from heated slabs. One of the major control problems in hot rolling mills are the looper and tension control loops because these have a significant impact on the dimensional quality of a strip and process stability. Moreover, the most difficult challenge in the controller design arises from the process interaction and uncertainty affecting these loops; uncertainty comes from several sources of disturbances and model mismatch. Recently, some authors have investigated the potential benefits of MPC (model predictive control). However, most authors used constrained optimisation based on nominal models and therefore, recursive feasibility and stability is not guaranteed for the uncertain case. The aim of this paper is to extend previous studies of MPC for rolling mills (Choi, Rossiter and Fleming, 2004) to the robust case as well as to evaluate the efficacy of a recently proposed robust MPC (RMPC) (Pluymers, Rossiter, Suykens and De Moor, 2005) design on a multi-dimensional process