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

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.
Comment: 7 pages, 4 figures. This paper is accepted and presented at the 2021 IEEE Conference on Decision and Control (CDC)