This article presents a robust control strategy using Time-Optimal Model Predictive Control (TOMPC) for a two-level quantum system subject to bounded uncertainties. In this method, the control field is optimized over a finite horizon using a nominal quantum system as the reference and then the optimal control for the first time interval is applied and a projective measurement is implemented on the uncertain system. The new control field for the next time interval will be iteratively optimized based on the measurement result. We present theoretical results to guarantee the stability of the TOMPC algorithm. We also characterize the robustness and the convergence rate of the TOMPC strategy for the control of two-level systems. Numerical simulations further demonstrate that, in the presence of uncertainties, our quantum TOMPC algorithm enhances robustness and steers the state to the desired state with high fidelity. This work contributes to the progress of Model Predictive Control in quantum control and explores its potential in practical applications of quantum technology.This article presents a robust control strategy using Time-Optimal Model Predictive Control (TOMPC) for a two-level quantum system subject to bounded uncertainties. In this method, the control field is optimized over a finite horizon using a nominal quantum system as the reference and then the optimal control for the first time interval is applied and a projective measurement is implemented on the uncertain system. The new control field for the next time interval will be iteratively optimized based on the measurement result. We present theoretical results to guarantee the stability of the TOMPC algorithm. We also characterize the robustness and the convergence rate of the TOMPC strategy for the control of two-level systems. Numerical simulations further demonstrate that, in the presence of uncertainties, our quantum TOMPC algorithm enhances robustness and steers the state to the desired state with high fidelity. This work contributes to the progress of Model Predictive Control in quantum control and explores its potential in practical applications of quantum technology.

arXiv:2402.07396IEEE Transactions on Automatic ControlJan 1, 20261 citation

Differential Evolution with Equally-Mixed Strategies for Robust Control of Open Quantum Systems

Hailan Ma, Chunlin Chen, Daoyi Dong

Robust control of open quantum systems from one state to another is much more difficult than closed quantum systems as a result of system-environment interactions. In this paper, we adopt the sampling-based learning control approach with the motivation of utilizing some artificial samples instead of unknown uncertainties to design an optimal control field against parameter fluctuations. To enhance the learning performance, we introduce an improved differential evolution (DE) algorithm with equally-mixed strategies in the training step of the control design for open quantum systems. Numerical results verify the effectiveness of the proposed equally-mixed strategies DE (EMSDE) algorithm regarding the control design for open quantum systems with uncertainties.Robust control of open quantum systems from one state to another is much more difficult than closed quantum systems as a result of system-environment interactions. In this paper, we adopt the sampling-based learning control approach with the motivation of utilizing some artificial samples instead of unknown uncertainties to design an optimal control field against parameter fluctuations. To enhance the learning performance, we introduce an improved differential evolution (DE) algorithm with equally-mixed strategies in the training step of the control design for open quantum systems. Numerical results verify the effectiveness of the proposed equally-mixed strategies DE (EMSDE) algorithm regarding the control design for open quantum systems with uncertainties.

Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and CyberneticsOct 1, 201516 citations

Finite-time stabilization control of quantum systems

Sen Kuang, Xiaoke Guan, Daoyi Dong

arXiv:1910.00208AutomaticaNov 12, 202035 citations

Application of Sliding Mode Control & Observer to Stabilized Two-Level Quantum Systems

Kaydian Quintero, Bereket Berhane, Sergey V. Drakunov

State estimation and control of quantum systems present significant challenges due to the inherent noise, uncertainty, and non-linearity of quantum dynamics. In this paper, we propose the application of Sliding Mode Observers (SMOs) as a robust and efficient solution for the state estimation and control of finite dimensional quantum systems whose state is described by a density matrix $\rho$ . We demonstrate how these observers can be used to track quantum states accurately, despite the presence of measurement noise and system dynamics uncertainties. Furthermore, we introduce a control strategy that leverages the state estimates to stabilize the quantum system, ensuring desirable performance even under challenging conditions. Numerical simulations are provided to illustrate the effectiveness of the proposed methodology, showcasing improvements in system stability, accuracy of state estimation, and robustness to perturbations. The results highlight the potential of sliding mode observers as a viable tool for quantum control applications, including quantum information processing, quantum computing, and other emerging quantum technologies.State estimation and control of quantum systems present significant challenges due to the inherent noise, uncertainty, and non-linearity of quantum dynamics. In this paper, we propose the application of Sliding Mode Observers (SMOs) as a robust and efficient solution for the state estimation and control of finite dimensional quantum systems whose state is described by a density matrix$\rho$. We demonstrate how these observers can be used to track quantum states accurately, despite the presence of measurement noise and system dynamics uncertainties. Furthermore, we introduce a control strategy that leverages the state estimates to stabilize the quantum system, ensuring desirable performance even under challenging conditions. Numerical simulations are provided to illustrate the effectiveness of the proposed methodology, showcasing improvements in system stability, accuracy of state estimation, and robustness to perturbations. The results highlight the potential of sliding mode observers as a viable tool for quantum control applications, including quantum information processing, quantum computing, and other emerging quantum technologies.

IEEE Conference on Control Technology and Applications (CCTA)Aug 25, 20250 citations

Stability and optimality in feedback control of quantum systems

和記西尾

Jan 1, 20100 citations

\rho

. We demonstrate how these observers can be used to track quantum states accurately, despite the presence of measurement noise and system dynamics uncertainties. Furthermore, we introduce a control strategy that leverages the state estimates to stabilize the quantum system, ensuring desirable performance even under challenging conditions. Numerical simulations are provided to illustrate the effectiveness of the proposed methodology, showcasing improvements in system stability, accuracy of state estimation, and robustness to perturbations. The results highlight the potential of sliding mode observers as a viable tool for quantum control applications, including quantum information processing, quantum computing, and other emerging quantum technologies.