Wentao Tang

Orcid: 0000-0003-0816-2322

Affiliations:
  • North Carolina State University, Department of Chemical and Biomolecular Engineering, Raleigh, NC, USA
  • University of Minnesota, Minneapolis, MN, USA


According to our database1, Wentao Tang authored at least 20 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2023
Automatic decomposition of large-scale industrial processes for distributed MPC on the Shell-Yokogawa Platform for Advanced Control and Estimation (PACE).
Comput. Chem. Eng., October, 2023

The future of control of process systems.
Comput. Chem. Eng., October, 2023

Synthesis of Data-Driven Nonlinear State Observers using Lipschitz-Bounded Neural Networks.
CoRR, 2023

Optimal Design of Control-Lyapunov Functions by Semi-Infinite Stochastic Programming.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Dissipativity Learning Control through Estimation from Online Trajectories<sup>*</sup>.
Proceedings of the American Control Conference, 2023

Resolving large-scale control and optimization through network structure analysis and decomposition: A tutorial review.
Proceedings of the American Control Conference, 2023

2022
Data-Driven Control: Overview and Perspectives <sup>*</sup>.
Proceedings of the American Control Conference, 2022

2021
Dissipativity learning control (DLC): Theoretical foundations of input-output data-driven model-free control.
Syst. Control. Lett., 2021

Coordinating distributed MPC efficiently on a plantwide scale: The Lyapunov envelope algorithm.
Comput. Chem. Eng., 2021

Nonlinear state and parameter estimation using derivative information: A Lie-Sobolev approach.
Comput. Chem. Eng., 2021

2020
Fast and Stable Nonconvex Constrained Distributed Optimization: The ELLADA Algorithm.
CoRR, 2020

2019
A Bilevel Programming Approach to the Convergence Analysis of Control-Lyapunov Functions.
IEEE Trans. Autom. Control., 2019

Dissipativity learning control (DLC): A framework of input-output data-driven control.
Comput. Chem. Eng., 2019

Input-output data-driven control through dissipativity learning.
Proceedings of the 2019 American Control Conference, 2019

Distributed nonlinear model predictive control through accelerated parallel ADMM.
Proceedings of the 2019 American Control Conference, 2019

2018
Distributed adaptive dynamic programming for data-driven optimal control.
Syst. Control. Lett., 2018

Reprint of: Optimal decomposition for distributed optimization in nonlinear model predictive control through community detection.
Comput. Chem. Eng., 2018

Optimal decomposition for distributed optimization in nonlinear model predictive control through community detection.
Comput. Chem. Eng., 2018

Decomposing complex plants for distributed control: Perspectives from network theory.
Comput. Chem. Eng., 2018

The role of community structures in sparse feedback control.
Proceedings of the 2018 Annual American Control Conference, 2018


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