Hybrid Control of Uncertain Quantum Systems via Fuzzy Estimation and Quantum Reinforcement Learning

摘要：

A hybrid control approach for uncertain quantum systems is proposed using probabilistic fuzzy estimators (PFE) and quantum reinforcement learning (QRL). This hybrid control design involves coherent control with PFE and learning control via QRL. The problems of controlling a quantum system from an initial state to a pointed target state are studied in this paper, where we assume that the initial quantum state is a mixed state and the target quantum state is a controllable pure state within a wavefunction controllable subspace. First, the initial quantum system is controlled coherently with the help of a PFE. When the controlled system is estimated to be likely to collapse to an expected eigen state, trigger the measurement and the quantum system collapses to an eigen state in the wavefuntion controllable subspace with a high probability. Then the quantum system is driven to the target state with admissible controls, where the control sequence is learned and optimized with QRL. An example is presented and analyzed to demonstrate the control process.

关键词： Fuzzy Estimation Quantum Control Quantum Reinforcement Learning Uncertain

作者: CHEN Chunlin JIANG Frank DONG Daoyi

作者单位: Department of Control and System Engineering, Nanjing University, Nanjing 210093, P. R. China State School of Engineering and Information Technology, University of New South Wales at the Australian De State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, P. R. C

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 7177-7182

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）