Data-Driven Predictive Control for Continuous-Time Industrial Processes with Completely Unknown Dynamics
Optimization and Control
2020-12-08 v1 Systems and Control
Systems and Control
Abstract
This paper investigates the data-driven predictive control problems for a class of continuous-time industrial processes with completely unknown dynamics. The proposed approach employs the data-driven technique to get the system matrices online, using input-output measurements. Then, a model-free predictive control approach is designed to implement the receding-horizon optimization and realize the reference tracking. Feasibility of the proposed algorithm and stability of the closed-loop control systems are analyzed, respectively. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed approach.
Cite
@article{arxiv.2012.03452,
title = {Data-Driven Predictive Control for Continuous-Time Industrial Processes with Completely Unknown Dynamics},
author = {Yuanqiang Zhou and Dewei Li and Yugeng Xi},
journal= {arXiv preprint arXiv:2012.03452},
year = {2020}
}
Comments
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