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ORCIDMichael G. Forbes
Person information
- affiliation: Honeywell Process Solutions, North Vancouver, BC, Canada
- affiliation (former, PhD): University of Alberta, Department of Chemical & Materials Engineering, Edmonton, AB, Canada
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2020 – today
- 2024
[j7]Nathan P. Lawrence, Philip D. Loewen, Shuyuan Wang, Michael G. Forbes, R. Bhushan Gopaluni:
Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior. Autom. 164: 111642 (2024)- [c10]Nathan P. Lawrence, Philip D. Loewen, Shuyuan Wang, Michael G. Forbes, R. Bhushan Gopaluni:
Deep Hankel matrices with random elements. L4DC 2024: 1579-1591 - [i11]Nathan P. Lawrence, Philip D. Loewen, Shuyuan Wang, Michael G. Forbes, R. Bhushan Gopaluni:
Deep Hankel matrices with random elements. CoRR abs/2404.15512 (2024) - 2023
- [i10]Nathan P. Lawrence
, Philip D. Loewen, Shuyuan Wang, Michael G. Forbes, R. Bhushan Gopaluni:
A modular framework for stabilizing deep reinforcement learning control. CoRR abs/2304.03422 (2023) - [i9]Shuyuan Wang, Philip D. Loewen, Nathan P. Lawrence, Michael G. Forbes, R. Bhushan Gopaluni:
Reinforcement Learning with Partial Parametric Model Knowledge. CoRR abs/2304.13223 (2023) - [i8]Nathan P. Lawrence, Philip D. Loewen, Shuyuan Wang, Michael G. Forbes, R. Bhushan Gopaluni:
Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior. CoRR abs/2310.14098 (2023) - 2022
- [i7]Daniel G. McClement, Nathan P. Lawrence, Johan U. Backström, Philip D. Loewen, Michael G. Forbes, R. Bhushan Gopaluni:
Meta Reinforcement Learning for Adaptive Control: An Offline Approach. CoRR abs/2203.09661 (2022) - [i6]Daniel G. McClement, Nathan P. Lawrence, Michael G. Forbes, Philip D. Loewen, Johan U. Backström, R. Bhushan Gopaluni:
Meta-Reinforcement Learning for Adaptive Control of Second Order Systems. CoRR abs/2209.09301 (2022) - 2021
- [i5]Daniel G. McClement, Nathan P. Lawrence, Philip D. Loewen, Michael G. Forbes, Johan U. Backström, R. Bhushan Gopaluni:
A Meta-Reinforcement Learning Approach to Process Control. CoRR abs/2103.14060 (2021) - [i4]Nathan P. Lawrence, Philip D. Loewen, Michael G. Forbes, Johan U. Backström, R. Bhushan Gopaluni:
Almost Surely Stable Deep Dynamics. CoRR abs/2103.14722 (2021) - [i3]Nathan P. Lawrence, Michael G. Forbes, Philip D. Loewen, Daniel G. McClement, Johan U. Backström, R. Bhushan Gopaluni:
Deep Reinforcement Learning with Shallow Controllers: An Experimental Application to PID Tuning. CoRR abs/2111.07171 (2021) - 2020
- [j6]Qiugang Lu, Michael G. Forbes, Philip D. Loewen, Johan U. Backström, Guy Albert Dumont, R. Bhushan Gopaluni:
Support vector machine approach for model-plant mismatch detection. Comput. Chem. Eng. 133 (2020) - [c9]Nathan P. Lawrence, Philip D. Loewen, Michael G. Forbes, Johan U. Backström, R. Bhushan Gopaluni:
Almost Surely Stable Deep Dynamics. NeurIPS 2020 - [i2]Nathan P. Lawrence, Gregory E. Stewart, Philip D. Loewen, Michael G. Forbes, Johan U. Backström, R. Bhushan Gopaluni:
Reinforcement Learning based Design of Linear Fixed Structure Controllers. CoRR abs/2005.04537 (2020) - [i1]Nathan P. Lawrence, Gregory E. Stewart, Philip D. Loewen, Michael G. Forbes, Johan U. Backström, R. Bhushan Gopaluni:
Optimal PID and Antiwindup Control Design as a Reinforcement Learning Problem. CoRR abs/2005.04539 (2020)
2010 – 2019
- 2019
- [j5]Kai Wang, Michael G. Forbes, R. Bhushan Gopaluni, Junghui Chen, Zhihuan Song:
Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes. IEEE Access 7: 22554-22565 (2019) - [j4]Qiugang Lu, Philip D. Loewen, R. Bhushan Gopaluni, Michael G. Forbes, Johan U. Backström, Guy Albert Dumont, Michael S. Davies:
Identification of symmetric noncausal processes. Autom. 103: 515-530 (2019) - 2018
- [j3]Ning He, Xiaotao Liu, Michael G. Forbes, Johan U. Backström, Tongwen Chen:
Robust Tuning of Cross-Directional Model Predictive Controllers for Paper-Making Processes. IEEE Trans. Control. Syst. Technol. 26(5): 1619-1634 (2018) - 2017
- [j2]Qiugang Lu, Michael G. Forbes, R. Bhushan Gopaluni, Philip D. Loewen, Johan U. Backström, Guy Albert Dumont:
Performance Assessment of Cross-Directional Control for Paper Machines. IEEE Trans. Control. Syst. Technol. 25(1): 208-221 (2017) - [c8]Qiugang Lu, Lee D. Rippon, R. Bhushan Gopaluni, Michael G. Forbes, Philip D. Loewen, Johan U. Backström, Guy Albert Dumont:
Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines. ACC 2017: 2837-2842 - 2015
- [c7]Qiugang Lu, Lee D. Rippon, R. Bhushan Gopaluni, Michael G. Forbes, Philip D. Loewen, Johan U. Backström, Guy Albert Dumont:
Cross-directional controller performance monitoring for paper machines. ACC 2015: 4970-4975 - [c6]Mahdi Yousefi, Qiugang Lu, R. Bhushan Gopaluni, Philip D. Loewen, Michael G. Forbes, Guy Albert Dumont, Johan U. Backström:
Detecting model-plant mismatch without external excitation. ACC 2015: 4976-4981 - 2014
- [c5]Mahdi Yousefi, Michael G. Forbes, R. Bhushan Gopaluni, Philip D. Loewen, Guy Albert Dumont, Johan U. Backström:
Sensitivity of MIMO controller performance to model-plant mismatch, with applications to paper machine control. CCA 2014: 204-209 - [c4]Mahdi Yousefi, Michael G. Forbes, R. Bhushan Gopaluni, Guy Albert Dumont, Johan U. Backström, Ashish Malhotra:
Sensitivity of controller performance indices to model-plant mismatch: An application to paper machine control. ACC 2014: 3506-3511
2000 – 2009
- 2006
- [j1]Michael G. Forbes, J. Fraser Forbes, Martin Guay:
Controller Design for Discrete-Time Stochastic Processes With Nonquadratic Loss. Technometrics 48(3): 361-372 (2006) - 2004
- [c3]Michael G. Forbes, Martin Guay, J. Fraser Forbes:
Probabilistic control design for continuous-time stochastic nonlinear systems: a PDF-shaping approach. ISIC 2004: 132-136 - 2003
- [c2]Michael G. Forbes, J. Fraser Forbes, Martin Guay:
Regulatory control design for stochastic processes: shaping the probability density function. ACC 2003: 3998-4003 - [c1]Michael G. Forbes, J. Fraser Forbes, Martin Guay:
Control design for discrete-time stochastic nonlinear processes with a nonquadratic performance objective. CDC 2003: 4243-4248
Coauthor Index
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