Nonlinear model predictive control with polytopic invariant sets

Ellipsoidal invariant sets have been widely used as target sets in MPC. These sets can be computed by constructing appropriate Linear Difference Inclusions together with additional constraints to ensure that the ellipsoid lies within a given Inclusion Polytope. The choice of this polytope has a significant effect on the size of the computed ellipsoid, but the optimal inclusion polytope cannot in general be computed systematically. This paper shows that use of polytopic invariant sets overcomes this difficulty, resulting in larger stabilizable sets without loss of closed-loop performance. In the interests of online efficiency, consideration is focused on interpolation-based NMPC. Copyright c 2002 IFAC