Chen Chunlin, Wang Lin-Cheng, Wang Yuanlong
Department of Control and System Engineering, Nanjing University, Nanjing 210093, China.
ScientificWorldJournal. 2013 Aug 7;2013:869285. doi: 10.1155/2013/869285. eCollection 2013.
For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control) have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA), and reinforcement learning (RL) methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H(∞) control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.
对于大多数实际的量子控制系统而言，由于系统动力学或模型中不可避免地存在不确定性，实现鲁棒性和可靠性既重要又困难。三种典型的方法（例如，闭环学习控制、反馈控制和鲁棒控制）已被证明对解决这些问题有效。本文对量子系统的闭环和鲁棒控制进行了全面综述，并简要介绍了该研究领域的一些基本理论和方法，为感兴趣的读者提供进一步研究的总体思路。在量子系统的闭环学习控制领域，我们从探索量子控制景观的统一视角，综述并介绍了诸如基于梯度的方法、遗传算法（GA）和强化学习（RL）方法等学习控制方法。对于反馈控制方法，本文综述了三种控制策略，包括李雅普诺夫控制、基于测量的控制和相干反馈控制。然后回顾了量子鲁棒控制领域中的诸如H(∞)控制、滑模控制、量子风险敏感控制和量子系综控制等主题。本文最后展望了未来可能会吸引更多关注的研究方向。
