Quasi-Min-Max MPC for Nonlinear System via Embedding Approach

A quasi-min-max model predictive control (MPC) algorithm is proposed for constrained nonlinear system via an embedding approach. The nonlinear system can be approximated by a linear parameter varying (LPV) model. And a method based on invariant set is proposed for the embedding model to reduce the computational complexity. The proposed method constructs a one-step invariant set comprises an interpolation between several pre-computed invariant sets at each time instant. Then control law is obtained by solving a constrained QP problem, which is also useful for the nonlinear system. The performances of the approach are presented via an example.