Model Predictive Control of a class of Uncertain Nonlinear Discrete Time Systems: The LMI approach

Model predictive control (MPC) of linear systems is well stablished in the literature. However, The MPC design of nonlinear systems has many challenges and complex calculations due to the inclusion of non-convex optimization problem. This paper, proposes a new approach based on linear matrix inequality to solve the MPC problem with finite horizon for nonlinear uncertain systems which contain additive uncertainty. The proposed algorithm can be applied to a wide class of nonlinear systems and guarantees their stability. The performance and effectiveness of the proposed controller is illustrated with numerical examples.