Online trajectory optimization for nonlinear systems by the concept of a model control loop — Applied to the reaction wheel pendulum

This paper presents a solution for online optimization of reference trajectories for nonlinear tracking controllers. A Nonlinear Model Predictive Control (NMPC) algorithm is applied to control a model of the plant online to track the user references, e.g. step changes. The resulting state trajectories of the simulated model are used as a reference for a low level trajectory tracking controller that regulates the plant. Additionally, the control signals of this simulated closed loop can be used as feedforward control in the low level controller. This concept is called “model control loop”, that is a special form of a two-degree-of-freedom control. In this setup, the advantage of online trajectory optimization that NMPC offers is exploited, while the stability problem of NMPC due to long computation times is avoided. The method is applied to the reaction wheel pendulum, experimental results are presented.