Chao Shang
Orcid: 0000-0003-3905-4631Affiliations:
- Tsinghua University, Department of Automation, Beijing National Research Center for Information Science and Technology, Beijing, China
- Cornell University, Robert Frederick Smith School of Chemical and Biomolecular Engineering, Ithaca, NY, USA (2018)
- Tsinghua University, Department of Automation, Beijing, China (PhD 2016)
According to our database1,
Chao Shang
authored at least 40 papers
between 2014 and 2025.
Collaborative distances:
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Bibliography
2025
IEEE Trans. Autom. Control., February, 2025
A Novel Accuracy-Constrained Scheme for Efficient Trend Extraction of Industrial Time-Series Data.
IEEE Trans. Instrum. Meas., 2025
Dynamic-Inner White Component Analysis: A New Latent Variable Model for Dynamic Data Analytics and Process Monitoring.
IEEE Trans Autom. Sci. Eng., 2025
Computer-aided molecular design by aligning generative diffusion models: Perspectives and challenges.
Comput. Chem. Eng., 2025
Data-driven output prediction and control of stochastic systems: An innovation-based approach.
Autom., 2025
2024
IEEE Trans. Neural Networks Learn. Syst., May, 2024
Data-Driven Output Containment Control of Heterogeneous Multiagent Systems: A Hierarchical Scheme.
Proceedings of the 63rd IEEE Conference on Decision and Control, 2024
Data-Driven Fault Detection for Lithium-Ion Battery Packs via Behavioral System Representation.
Proceedings of the IEEE Conference on Control Technology and Applications, 2024
2023
From Generalized Gauss Bounds to Distributionally Robust Fault Detection With Unimodality Information.
IEEE Trans. Autom. Control., September, 2023
Semi-global fault-tolerant cooperative output regulation of heterogeneous multi-agent systems with actuator saturation.
Inf. Sci., September, 2023
Efficient Relay Autotuner of Industrial Controllers via Rank-Constrained Identification of Low-Order Time-Delay Models.
IEEE Trans. Control. Syst. Technol., July, 2023
Just-In-Time Learning Based Functional Spectral Data Modeling for In-Situ Measurement of Slurry Component Concentrations via Infrared Spectroscopy.
IEEE Trans. Instrum. Meas., 2023
Fault Detection for Nonlinear Dynamic Systems With Consideration of Modeling Errors: A Data-Driven Approach.
IEEE Trans. Cybern., 2023
Data-Driven Predictive Control Using Closed-Loop Data: An Instrumental Variable Approach.
IEEE Control. Syst. Lett., 2023
Accelerated Nonconvex ADMM with Self-Adaptive Penalty for Rank-Constrained Model Identification.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
Data-Driven Safe Controller Synthesis for Deterministic Systems: A Posteriori Method With Validation Tests.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
2022
Variational PLS-Based Calibration Model Building With Semi-Supervised Learning for Moisture Measurement During Fluidized Bed Drying by NIR Spectroscopy.
IEEE Trans. Instrum. Meas., 2022
Distributionally robust chance constraint with unimodality-skewness information and conic reformulation.
Oper. Res. Lett., 2022
2021
A Holistic Probabilistic Framework for Monitoring Nonstationary Dynamic Industrial Processes.
IEEE Trans. Control. Syst. Technol., 2021
IEEE Trans. Autom. Control., 2021
Multiple kernel learning-aided robust optimization: Learning algorithm, computational tractability, and usage in multi-stage decision-making.
Eur. J. Oper. Res., 2021
A deep learning-based robust optimization approach for refinery planning under uncertainty.
Comput. Chem. Eng., 2021
Autom., 2021
2020
Robust Model Predictive Control of Irrigation Systems With Active Uncertainty Learning and Data Analytics.
IEEE Trans. Control. Syst. Technol., 2020
Theoretical Exploration of Irrigation Control for Stem Water Potential through Model Predictive Control.
Proceedings of the 2020 American Control Conference, 2020
2019
Data-Driven Distributionally Robust Shortest Path Problem Using the Wasserstein Ambiguity Set.
Proceedings of the 15th IEEE International Conference on Control and Automation, 2019
Proceedings of the 15th IEEE International Conference on Control and Automation, 2019
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019
Robust Constrained Model Predictive Control of Irrigation Systems Based on Data-Driven Uncertainty Set Constructions.
Proceedings of the 2019 American Control Conference, 2019
2018
IEEE Trans. Ind. Electron., 2018
A data-driven robust optimization approach to scenario-based stochastic model predictive control.
CoRR, 2018
Comput. Chem. Eng., 2018
Dynamic Soft Sensor Based on Impulse Response Template and Deep Neural Network for Industrial Processes.
Proceedings of the Fuzzy Systems and Data Mining IV, 2018
Chance Constrained Model Predictive Control via Active Uncertainty Set Learning and Calibration.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Proceedings of the 2018 Annual American Control Conference, 2018
2017
Automatic hyper-parameter tuning for soft sensor modeling based on dynamic deep neural network.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017
2015
Extracting latent dynamics from process data for quality prediction and performance assessment via slow feature regression.
Proceedings of the American Control Conference, 2015
Proceedings of the American Control Conference, 2015
2014
Novel Bayesian Framework for Dynamic Soft Sensor Based on Support Vector Machine With Finite Impulse Response.
IEEE Trans. Control. Syst. Technol., 2014