Data-Driven Robust Chance Constrained Problems: A Mixture Model Approach
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Optimization Theory and Applications"
DOI: 10.1007/s10957-018-1376-4
Abstract: This paper discusses the mixture distribution-based data-driven robust chance constrained problem. We construct a data-driven mixture distribution-based uncertainty set from the perspective of simultaneously estimating higher-order moments. Then, we derive a reformulation of the data-driven… read more here.
Keywords: constrained problems; chance constrained; data driven; driven robust ... See more keywords
Deep Learning Driven 3D Robust Beamforming for Secure Communication of UAV Systems
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2021.3075996
Abstract: Beamforming is a promising technique to enhance the security of wireless transmission, while the optimal beamforming design with partial channel state informing (CSI) is challenging. This letter develops a three-dimensional (3D) robust beamforming method for… read more here.
Keywords: communication; driven robust; robust beamforming; deep learning ... See more keywords
Semiclosed Greenhouse Climate Control Under Uncertainty via Machine Learning and Data-Driven Robust Model Predictive Control
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Control Systems Technology"
DOI: 10.1109/tcst.2021.3094999
Abstract: This work proposes a novel data-driven robust model predictive control (DDRMPC) framework for automatic control of greenhouse in-door climate. The framework integrates dynamic control models of greenhouse temperature, humidity, and CO2 concentration level with data-driven… read more here.
Keywords: greenhouse; climate; uncertainty; control ... See more keywords