Real-time MHE-based nonlinear MPC of a Pendubot system

This paper addresses the real-time optirnal control of a Pendubot using nonlinear model predictive control (NMPC) combined with nonlinear moving horizon estimation (MHE). This fast, undo-actuated nonlinear mechatronic System apparently poses a challenging benefit mark problem that may benefit from a nonlinear optimization scheme. To overcome the related computational difficulties we make use of the ACADO Code Generation tool allowing to export, a highly efficient Gauss-Newton real-time iteration algorithm tailored to the nonlinear optimal control and estimation problem while respecting the imposed constraints. We show experimental results illustrating the overall Hosed-loop control performance, as well as the advantages of the nonlinear MHE--based NMPC scheme. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.