Open AccessSampling‐based learning control of quantum systems via path planning
Author(s) -
Chen Chunlin,
Long Ruixing,
Qi Bo,
Dong Daoyi
Publication year - 2014
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0320
Subject(s) - sampling (signal processing) , computer science , path (computing) , control theory (sociology) , motion planning , control (management) , quantum , control engineering , artificial intelligence , engineering , computer vision , robot , physics , filter (signal processing) , quantum mechanics , programming language
Robust control design is a central problem for quantum systems in practical implementation and applications. In this study, the authors present a systematic methodology of sampling‐based learning control via path planning for state transfer of quantum systems with uncertainties and bounded controls. The authors formulate the control problem of a quantum system with bounded uncertainties as the problem of steering this system to a target state with bounded controls via an optimised evolution path to achieve a satisfactory level of fidelity. To find the optimised path (controls), the authors present a combined design method of sampling‐based learning control and path planning. The numerical results on an example of a four‐level quantum system show the effectiveness of the proposed learning control design method. The method provides a useful design approach for learning control of quantum systems with uncertainties.