Nonlinear Model Predictive Controller Toolbox Master’s Thesis in the Master’s programme in Systems, Control and Mechatronics

Model Predictive Control (MPC) is an optimal control method. At each instant of time, a per-formance index is minimized with respect to a sequence of nominal control inputs and the first optimal control inputs are applied to the plant. At the next time step, the optimization problem is formulated and solved based on new estimates of states. MPC for nonlinear systems can lead to complex optimization problems, which can be computationally demanding and prevents the real-time execution. In this thesis, we describe various low complexity computational schemes for Nonlinear (NL) MPC controller