A proposal of adaptive parameter tuning for robust stabilizing control of $N$--level quantum angular momentum systems

TL;DR

This paper introduces an adaptive parameter tuning algorithm to enhance the robustness of quantum feedback control for $N$-level quantum angular momentum systems, ensuring convergence to the target state despite uncertainties.

Contribution

It presents a novel adaptive tuning method that improves the robustness and convergence properties of existing quantum stabilizing controllers.

Findings

Ensures local convergence to the target state.

Numerical experiments show potential for global convergence with proper parameters.

Builds on and extends previous robust stabilizing control methods.

Abstract

Stabilizing control synthesis is one of the central subjects in control theory and engineering, and it always has to deal with unavoidable uncertainties in practice. In this study, we propose an adaptive parameter tuning algorithm for robust stabilizing quantum feedback control of $N$-level quantum angular momentum systems with a robust stabilizing controller proposed by [Liang, Amini, and Mason, SIAM J. Control Optim., 59 (2021), pp. 669-692]. The proposed method ensures local convergence to the target state. Besides, numerical experiments indicate its global convergence if the learning parameters are adequately determined.