Regulatory control design for stochastic processes: shaping the probability density function. - Michael G. Forbes; J. Fraser Forbes; Martin Guay (ACC, 2003)

Control design for discrete-time stochastic nonlinear processes with a nonquadratic performance objective. - Michael G. Forbes; J. Fraser Forbes; Martin Guay (CDC, 2003)

Probabilistic control design for continuous-time stochastic nonlinear systems: a PDF-shaping approach. - Michael G. Forbes; Martin Guay; J. Fraser Forbes (ISIC, 2004)

Controller Design for Discrete-Time Stochastic Processes With Nonquadratic Loss. - Michael G. Forbes; J. Fraser Forbes; Martin Guay (Technometrics, 2006)

Sensitivity of MIMO controller performance to model-plant mismatch, with applications to paper machine control. - Mahdi Yousefi; Michael G. Forbes; R. Bhushan Gopaluni; Philip D. Loewen; Guy Albert Dumont; Johan U. Backström (CCA, 2014)

Sensitivity of controller performance indices to model-plant mismatch: An application to paper machine control. - Mahdi Yousefi; Michael G. Forbes; R. Bhushan Gopaluni; Guy Albert Dumont; Johan U. Backström; Ashish Malhotra (ACC, 2014)

Cross-directional controller performance monitoring for paper machines. - Qiugang Lu; Lee D. Rippon; R. Bhushan Gopaluni; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont (ACC, 2015)

Detecting model-plant mismatch without external excitation. - Mahdi Yousefi; Qiugang Lu; R. Bhushan Gopaluni; Philip D. Loewen; Michael G. Forbes; Guy Albert Dumont; Johan U. Backström (ACC, 2015)

Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines. - Qiugang Lu; Lee D. Rippon; R. Bhushan Gopaluni; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont (ACC, 2017)

Performance Assessment of Cross-Directional Control for Paper Machines. - Qiugang Lu; Michael G. Forbes; R. Bhushan Gopaluni; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont (IEEE Trans. Control. Syst. Technol., 2017)

Robust Tuning of Cross-Directional Model Predictive Controllers for Paper-Making Processes. - Ning He; Xiaotao Liu; Michael G. Forbes; Johan U. Backström; Tongwen Chen (IEEE Trans. Control. Syst. Technol., 2018)

Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes. - Kai Wang 024; Michael G. Forbes; R. Bhushan Gopaluni; Junghui Chen; Zhihuan Song (IEEE Access, 2019)

Identification of symmetric noncausal processes. - Qiugang Lu; Philip D. Loewen; R. Bhushan Gopaluni; Michael G. Forbes; Johan U. Backström; Guy Albert Dumont; Michael S. Davies (Autom., 2019)

Almost Surely Stable Deep Dynamics. - Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (NeurIPS, 2020)

Support vector machine approach for model-plant mismatch detection. - Qiugang Lu; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont; R. Bhushan Gopaluni (Comput. Chem. Eng., 2020)

Reinforcement Learning based Design of Linear Fixed Structure Controllers. - Nathan P. Lawrence; Gregory E. Stewart; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2020)

Optimal PID and Antiwindup Control Design as a Reinforcement Learning Problem. - Nathan P. Lawrence; Gregory E. Stewart; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2020)

A Meta-Reinforcement Learning Approach to Process Control. - Daniel G. McClement; Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2021)

Deep Reinforcement Learning with Shallow Controllers: An Experimental Application to PID Tuning. - Nathan P. Lawrence; Michael G. Forbes; Philip D. Loewen; Daniel G. McClement; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2021)

Meta Reinforcement Learning for Adaptive Control: An Offline Approach. - Daniel G. McClement; Nathan P. Lawrence; Johan U. Backström; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni (CoRR, 2022)

Meta-Reinforcement Learning for Adaptive Control of Second Order Systems. - Daniel G. McClement; Nathan P. Lawrence; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2022)

A modular framework for stabilizing deep reinforcement learning control. - Nathan P. Lawrence; Philip D. Loewen; Shuyuan Wang; Michael G. Forbes; R. Bhushan Gopaluni (CoRR, 2023)

Reinforcement Learning with Partial Parametric Model Knowledge. - Shuyuan Wang; Philip D. Loewen; Nathan P. Lawrence; Michael G. Forbes; R. Bhushan Gopaluni (CoRR, 2023)

Guiding Reinforcement Learning with Incomplete System Dynamics. - Shuyuan Wang; Jingliang Duan; Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni; Lixian Zhang (IROS, 2024)

Deep Hankel matrices with random elements. - Nathan P. Lawrence; Philip D. Loewen; Shuyuan Wang; Michael G. Forbes; R. Bhushan Gopaluni (L4DC, 2024)

Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior. - Nathan P. Lawrence; Philip D. Loewen; Shuyuan Wang; Michael G. Forbes; R. Bhushan Gopaluni (Autom., 2024)

A view on learning robust goal-conditioned value functions: Interplay between RL and MPC. - Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni; Ali Mesbah 002 (CoRR, 2025)

DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation. - Shuyuan Wang; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni; Wei Pan (CoRR, 2025)