Fast nonlinear model predictive control via partial enumeration

Abstract

In this work, we consider the problem of fast, accurate control of a robot with constrained dynamics. We present a new nonlinear model predictive control (MPC) technique, Nonlinear Partial Enumeration (NPE), that combines online and offline computation in a nonlinear version of the partial enumeration method for MPC, thereby dramatically decreasing the compute time per control iteration. We apply NPE to the problem of MAV flight and demonstrate through a set of simulation trials that NPE outperforms other fast control methodologies during aggressive motion and enables the system to learn a reusable set of local feedback controllers that enable more efficient operation over time.