%A Runze GAO, Yuanqing XIA, Li DAI, Zhongqi SUN, Yufeng ZHAN %T Design and implementation of data-driven predictive cloud control system %0 Journal Article %D 2022 %J Journal of Systems Engineering and Electronics %R 10.23919/JSEE.2022.000146 %P 1258-1268 %V 33 %N 6 %U {https://www.jseepub.com/CN/abstract/article_9000.shtml} %8 2022-12-24 %X

The rapid increase of the scale and the 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 complex large-scale control missions by using sufficient computing resources. However, the computing ability enables more complex devices and more data to be involved and most of the data have not been fully utilized. Meanwhile, it is even impossible to obtain an accurate model of each device in the complex control systems for the model-based control algorithms. Therefore, motivated by the above reasons, we propose a data-driven predictive cloud control system. To achieve the proposed system, a practical data-driven predictive cloud control testbed is established and together a cloud-edge communication scheme is developed. Finally, the simulations and experiments demonstrate the effectiveness of the proposed system.