Michael G. Forbes
Affiliations:- Honeywell Process Solutions, North Vancouver, BC, Canada
- University of Alberta, Department of Chemical & Materials Engineering, Edmonton, AB, Canada (former, PhD)
According to our database1,
Michael G. Forbes
authored at least 25 papers
between 2003 and 2024.
Collaborative distances:
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Bibliography
2024
Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior.
Autom., 2024
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024
2023
2022
2021
Deep Reinforcement Learning with Shallow Controllers: An Experimental Application to PID Tuning.
CoRR, 2021
2020
CoRR, 2020
CoRR, 2020
Comput. Chem. Eng., 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes.
IEEE Access, 2019
2018
Robust Tuning of Cross-Directional Model Predictive Controllers for Paper-Making Processes.
IEEE Trans. Control. Syst. Technol., 2018
2017
IEEE Trans. Control. Syst. Technol., 2017
Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines.
Proceedings of the 2017 American Control Conference, 2017
2015
Proceedings of the American Control Conference, 2015
Proceedings of the American Control Conference, 2015
2014
Sensitivity of controller performance indices to model-plant mismatch: An application to paper machine control.
Proceedings of the American Control Conference, 2014
Sensitivity of MIMO controller performance to model-plant mismatch, with applications to paper machine control.
Proceedings of the 2014 IEEE Conference on Control Applications, 2014
2006
Technometrics, 2006
2004
Probabilistic control design for continuous-time stochastic nonlinear systems: a PDF-shaping approach.
Proceedings of the Intelligent Control, 2004
2003
Control design for discrete-time stochastic nonlinear processes with a nonquadratic performance objective.
Proceedings of the 42nd IEEE Conference on Decision and Control, 2003
Regulatory control design for stochastic processes: shaping the probability density function.
Proceedings of the American Control Conference, 2003