Nowadays, the rapid increases of the scale and complexity of the controlled plants bring new challenges such as computing power and storage for conventional control systems. Cloud computing is concerned as a powerful solution to handle the complex large-scale control missions using sufficient computing resources. However, the developed computing ability enables more complex devices and mass data being involved and thus the applications of model-based algorithms are constrained. Motivated by the above, we propose an original data-driven predictive cloud control system. To achieve the proposed system, a practical data-driven predictive cloud control platform rather than only a numerical simulator is established and together a cloud-edge communication scheme is developed. Finally, the verification of simulations and experiments as well as discussions demonstrate the effectiveness of the proposed system.
@article{arxiv.2112.14347,
title = {Design and Implementation of Data-driven Predictive Cloud Control System},
author = {Runze Gao and Yuanqing Xia and Li Dai and Zhongqi Sun},
journal= {arXiv preprint arXiv:2112.14347},
year = {2023}
}