Global low-rank enhancement of decentralized control for large-scale systems

This note proposes a new control strategy which is computationally attractive for systems of large dimensions. The main idea is to supplement decentralized feedback with a global additive term, which is computed as a product of two low-rank matrices. This feature is of critical importance for systems that cannot be adequately stabilized using standard decentralized control. The low-rank matrices can be efficiently obtained using linear matrix inequalities, and the resulting control is suitable for implementation in a multiprocessor environment. Simulations on a platoon of vehicles demonstrate that such a control can significantly improve the robustness of the closed-loop system with respect to uncertain nonlinearities.