Wee Chin Wong

发表

DISTURBANCE MODELING FOR PROCESS CONTROL VIA HIDDEN MARKOV MODELS

Jay H. Lee, Wee Chin Wong, 2007 .

Improved disturbance and fault signal modeling via Hidden Markov Models

Wee Chin Wong, Jay H. Lee, Jay H. Lee, 2011, 2011 International Symposium on Advanced Control of Industrial Processes (ADCONIP).

A reinforcement learning-based scheme for adaptive optimal control of linear stochastic systems

J.H. Lee, Wee Chin Wong, Jay H. Lee, 2008, 2008 American Control Conference.

Fault Detection in Process Systems using Hidden Markov Disturbance Models

Wee Chin Wong, Jay H. Lee, Jay H. Lee, 2009 .

Hybrid cybernetic model-based simulation of continuous production of lignocellulosic ethanol: Rejecting abruptly changing feed conditions

Jay H. Lee, Doraiswami Ramkrishna, Wee Chin Wong, 2010 .

Realistic disturbance modeling using Hidden Markov Models: Applications in model-based process control

Jay H. Lee, Wee Chin Wong, Jay H. Lee, 2009 .

Estimation and control of jump stochastic systems

Wee Chin Wong, 2009 .

A reinforcement learning‐based scheme for direct adaptive optimal control of linear stochastic systems

Wee Chin Wong, JayHyung Lee, 2010 .

Hydrogen value chain and fuel cells within hybrid renewable energy systems: Advanced operation and control strategies

Wee Chin Wong, Xiaonan Wang, Anikesh Kumar, 2019, Applied Energy.

Recurrent Neural Network-based Model Predictive Control for Continuous Pharmaceutical Manufacturing pdf

Jiali Li, Wee Chin Wong, Xiaonan Wang, 2018, Mathematics.

A Hidden Markov disturbance model for Offset-free linear model predictive control

Jay H. Lee, Wee Chin Wong, Jay H. Lee, 2008 .

Approximate dynamic programming approach for process control

Wee Chin Wong, Jay H. Lee, 2009 .

Postdecision-State-Based Approximate Dynamic Programming for Robust Predictive Control of Constrained Stochastic Processes

Wee Chin Wong, Jay H. Lee, 2011 .

Fault Detection and Diagnosis Using Hidden Markov Disturbance Models

Wee Chin Wong, Jay H. Lee, 2010 .

An integrated approach for machine-learning-based system identification of dynamical systems under control: application towards the model predictive control of a highly nonlinear reactor system

Wee Chin Wong, Xiaonan Wang, Ewan Chee, 2021, Frontiers of Chemical Science and Engineering.