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arXiv 2603.22653eess.SYcs.SY
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具有量子加密的显式模型预测控制

Explicit Model Predictive Control with Quantum Encryption

Australian Centre for Robotics, School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney(悉尼大学航空航天、机械与机电工程学院澳大利亚机器人中心);State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University(浙江大学控制科学与工程学院工业控制技术国家重点实验室);School of Electrical and Computer Engineering, The University of Sydney(悉尼大学电气与计算机工程学院)

Yingjie Mi, Zihao Ren, Lei Wang, Daniel E. Quevedo, Guodong Shi

AI总结:

本文研究了基于云架构的量子加密显式MPC,通过离线求解有限时间二次MPC问题获得分段仿射控制器,利用量子密钥分发保护的量子密钥加密传感器与执行器间的在线控制评估,提出轻量级加密显式MPC协议,证明了明文控制动作的精确恢复并分析了计算效率。

摘要:

本文研究了基于云架构的量子加密显式MPC,用于受约束的离散时间线性系统。通过离线求解有限时间二次MPC问题,获得分段仿射控制器。利用由贝尔对生成并由量子密钥分发保护的量子密钥,加密传感器与执行器之间的在线控制评估。基于此架构,我们开发了轻量级加密显式MPC协议,证明了明文控制动作的精确恢复,并分析了其计算效率。数值结果表明,该方法的在线复杂度低于经典加密MPC,同时讨论了系统数据和控制输入的保密性。

英文摘要:

This paper studies quantum-encrypted explicit MPC for constrained discrete-time linear systems in a cloud-based architecture. A finite-horizon quadratic MPC problem is solved offline to obtain a piecewise-affine controller. Shared quantum keys generated from Bell pairs and protected by quantum key distribution are used to encrypt the online control evaluation between the sensor and actuator. Based on this architecture, we develop a lightweight encrypted explicit MPC protocol, prove exact recovery of the plaintext control action, and characterize its computational efficiency. Numerical results demonstrate lower online complexity than classical encrypted MPC, while security is discussed in terms of confidentiality of plant data and control inputs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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