Sensitivity-Based Distributed NMPC: Experimental Results for a Levitating Planar Motion System

Abstract

This brief presents the experimental results of a sensitivity-based distributed nonlinear model predictive (DMPC) scheme applied to a multiagent levitating planar motion system. The algorithm is based on first-order sensitivities such that the central optimal control problem (OCP) is solved cooperatively and in parallel on distributed hardware with networked communication. The experiments consist of a leader-follower scenario, a distribution problem, formation control, and cooperative load transport. The scenarios include couplings in cost functions, constraints, and dynamics in addition to inhomogeneous and nonlinear agent dynamics providing a challenging validation environment. The results showcase the applicability of DMPC to a wide range of classical distributed control problems and demonstrate the real-time capability of the proposed approach.