Nonlinear Model Predictive Control with Discrete Mechanics and Optimal Control

Abstract

In this contribution, we propose a novel nonlinear Model Predictive Control (NMPC) formulation based on the optimal control method Discrete Mechanics and Optimal Control (DMOC). We discuss the properties of the novel approach and compare it with the standard NMPC formulation based on the Multiple-Shooting method using numerical simulations. We also consider the real-time application of the NMPC algorithm by extending the DMOC based NMPC using the Real-Time Iteration scheme. We apply the extended NMPC controller to the swing-up and stabilization task of a double pendulum on a cart with limited rail length to show its capability for controlling nonlinear dynamical systems with input and state constraints.