Robust Stabilization of Atmospheric Carbon within a Family of Uncertain Carbon Cycle Dynamics
Abstract
A recently developed robust stabilization method for uncertain dynamical systems is applied to the problem of stabilizing the atmospheric carbon concentration. The underlying uncertain carbon cycle dynamics is treated as a class of deterministic nonlinear dynamical systems, containing the .real. one, which is unknown. The stabilization methodology incorporates a special learning mechanism allowing to reduce the uncertainty. Relations between the learning rate and parameters of the emission control strategy are analyzed. The analysis is based on numerical simulations using, among others, basic IPCC emission scenarios.