Time-Optimal nonlinear model predictive control with minimal control interventions

This paper presents a novel approach for time-optimal model predictive control. In contrast to a global uniform time scaling, the underlying optimal control problem rests upon a dynamic, local temporal discretization of the shooting grid. The approach seeks for a grid partition with minimum overall transition time. Furthermore, a multi-stage optimization iteratively adapts the number of grid points during runtime to achieve a minimum number of control interventions. A comparative analysis with previous approaches for three nonlinear control problems demonstrates the superiority of the proposed scheme. The feasibility is experimentally demonstrated for position control of a servo drive operated at 200 Hz.