Distributed Multiple Shooting for Optimal Control of Large Interconnected Systems

Large interconnected systems consist of a multitude of subsystems with their own dynamics, but coupled with each other via input-output connections. Each subsystem is typically modelled by ordinary differential equations or differential-algebraic equations. Simulation and optimal control of such systems pose a challenge both with respect to CPU time and memory requirements. We address optimal control of such systems by applying “distributed multiple shooting”, a generalization of the direct multiple shooting method, which uses the decomposable structure of the system in order to obtain a highly parallel algorithm. The interconnections are allowed to be infeasible during the iterations but are driven to feasibility by a Newtontype optimization algorithm. We evaluate the performance of the distributed multiple shooting method on a large scale estimation problem.