Wentao Tang

Automatic decomposition of large-scale industrial processes for distributed MPC on the Shell-Yokogawa Platform for Advanced Control and Estimation (PACE)

COMPUTERS & CHEMICAL ENGINEERING, 178.

Data-driven state observation for nonlinear systems based on online learning

AICHE JOURNAL, 8.

The future of control of process systems

COMPUTERS & CHEMICAL ENGINEERING, 178.

Coordinating distributed MPC efficiently on a plantwide scale: The Lyapunov envelope algorithm

Computers & Chemical Engineering, 155, 107532.

Dissipativity learning control (DLC): Theoretical foundations of input–output data-driven model-free control

Systems & Control Letters, 147, 104831.

Fast and stable nonconvex constrained distributed optimization: the ELLADA algorithm

Optimization and Engineering, 23(1), 259–301.

Nonlinear state and parameter estimation using derivative information: A Lie-Sobolev approach

Computers & Chemical Engineering, 151, 107369.

Stochastic blockmodeling for learning the structure of optimization problems

AIChE Journal, 68(6).

A Bilevel Programming Approach to the Convergence Analysis of Control-Lyapunov Functions

IEEE Transactions on Automatic Control, 64(10), 4174–4179.

DeCODe: a community-based algorithm for generating high-quality decompositions of optimization problems

Optimization and Engineering, 20(4), 1067–1084.

Decomposition of control and optimization problems by network structure: Concepts, methods, and inspirations from biology

AIChE Journal, 65(10).

Dissipativity learning control (DLC): A framework of input–output data-driven control

Computers & Chemical Engineering, 130, 106576.

Distributed control and optimization of process system networks: A review and perspective

Chinese Journal of Chemical Engineering, 27(7), 1461–1473.

Distributed decision making for intensified process systems

Current Opinion in Chemical Engineering, 25, 75–81.

Topology Effects on Sparse Control of Complex Networks with Laplacian Dynamics

Scientific Reports, 9(1).

Decomposing complex plants for distributed control: Perspectives from network theory

Computers & Chemical Engineering, 114, 43–51.

Distributed adaptive dynamic programming for data-driven optimal control

Systems & Control Letters, 120, 36–43.

Network decomposition for distributed control through community detection in input–output bipartite graphs

Journal of Process Control, 64, 7–14.

Optimal decomposition for distributed optimization in nonlinear model predictive control through community detection

Computers & Chemical Engineering, 111, 43–54.

Relative time‐averaged gain array (RTAGA) for distributed control‐oriented network decomposition

AIChE Journal, 64(5), 1682–1690.

Control configuration synthesis using agglomerative hierarchical clustering: A graph-theoretic approach

Journal of Process Control, 46, 43–54.