Abstract

Co-authors: Matthew Grace (Sandia National Laboratories), Constantin Brif (Sandia National Laboratories), Hersch Rabitz (Princeton University)

In a 1985 paper in Optics News entitled ``Quantum Mechanical Computers,'' Richard Feynman described how a computer could be built upon the mathematical principles of quantum mechanics. But he also heralded the difficulties in an actual physical implementation: ``This computer seems to be very delicate and these imperfections may produce considerable havoc.'' This talk will describe our on-going efforts to alleviate the potential ``havoc'' by appealing to robust control design, both model-based and data-based. The model-based approach relies on uncertainty modeling, i.e., values of parameters and noise sources in the model are unknown but contained in bounded sets. Sequential convex programming (SCP) is used to find controls which maximize fidelity despite the uncertainty. From an available set of input/observable pairs, the same type of model is used to estimate fidelity as well as refine knowledge about uncertain parameters, thereby leading to a more robust control providing increased performance.