In data-driven predictive cloud control tasks, the privacy of data stored and used in cloud services could be leaked to malicious attackers or curious eavesdroppers. Homomorphic encryption technique could be used to protect data privacy while allowing computation. However, extra errors are introduced by the homomorphic encryption extension to ensure the privacy-preserving properties, and the real number truncation also brings uncertainty. Also, process and measure noise existed in system input and output may bring disturbance. In this work, a data-driven predictive cloud controller is developed based on homomorphic encryption to protect the cloud data privacy. Besides, a disturbance observer is introduced to estimate and compensate the encrypted control signal sequence computed in the cloud. The privacy of data is guaranteed by encryption and experiment results show the effect of our cloud-edge cooperative design.

翻译：在数据驱动预测云控制任务中，云服务中存储和使用的数据隐私可能泄露给恶意攻击者或好奇的窃听者。同态加密技术可在保护数据隐私的同时允许计算，但为确保隐私保护属性，同态加密扩展会引入额外误差，且实数截断也会带来不确定性。此外，系统输入输出中的过程噪声与测量噪声可能产生扰动。本文基于同态加密技术设计了数据驱动预测云控制器，以保护云端数据隐私；同时引入扰动观测器，对云端计算的加密控制信号序列进行估计与补偿。数据隐私通过加密得到保障，实验结果验证了云边协同设计的有效性。