Sensitivity-based distributed model predictive control: synchronous and asynchronous execution compared to ADMM

Abstract

Abstract This paper presents synchronous and asynchronous formulations of a sensitivity-based algorithm for solving distributed continuous-time nonlinear optimal control problems with a neighbor-affine structure. Sensitivities are defined in an optimal control context and utilized to ensure coordination between agents. By using delayed data in the asynchronous formulation, idle times of agents are reduced and faster execution of the algorithm is achieved. The convergence behavior w.r.t. topology and coupling strength is investigated in a numerical simulation and the execution time is evaluated on distributed hardware with communication over TCP in comparison to the alternating direction method of multipliers (ADMM) algorithm.