  This paper presents a computationally efficient solution for constraint
management of multi-input and multi-output (MIMO) systems. The solution,
referred to as the Decoupled Reference Governor (DRG), maintains the
highly-attractive computational features of Scalar Reference Governors (SRG)
while having performance comparable to Vector Reference Governors (VRG). DRG is
based on decoupling the input-output dynamics of the system, followed by the
deployment of a bank of SRGs for each decoupled channel. We present two
formulations of DRG: DRG-tf, which is based on system decoupling using transfer
functions, and DRG-ss, which is built on state feedback decoupling. A detailed
set-theoretic analysis of DRG, which highlights its main characteristics, is
presented. We also show a quantitative comparison between DRG and the VRG to
illustrate the computational advantages of DRG. The robustness of this approach
to disturbances and uncertainties is also investigated.
