Zhong-Gai Zhao
Orcid: 0000-0002-4508-4979
According to our database1,
Zhong-Gai Zhao
authored at least 17 papers
between 2004 and 2024.
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Collaborative distances:
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Bibliography
2024
Reinforcement Learning for Finite-Horizon H∞ Tracking Control of Unknown Discrete Linear Time-Varying System.
IEEE Trans. Syst. Man Cybern. Syst., October, 2024
Optimal Control of Two-Dimensional Roesser Model: Solution Based on Reinforcement Learning.
IEEE Trans. Autom. Control., August, 2024
2023
Sensitivity analysis of the penicillin fermentation process model based on LHS-EPRCC.
Comput. Chem. Eng., November, 2023
2022
Latent variable point-to-point iterative learning model predictive control via reference trajectory updating.
Eur. J. Control, 2022
2021
Comput. Chem. Eng., 2021
2018
Process Modeling and Monitoring With Incomplete Data Based on Robust Probabilistic Partial Least Square Method.
IEEE Access, 2018
2014
Concurrent PLS-based process monitoring with incomplete input and quality measurements.
Comput. Chem. Eng., 2014
2013
Comput. Chem. Eng., 2013
Comput. Chem. Eng., 2013
Ellipsoidal set based robust particle filtering for recursive Bayesian state estimation.
Proceedings of the 10th IEEE International Conference on Control and Automation, 2013
2012
Proceedings of the 15th International Conference on Information Fusion, 2012
2008
Proceedings of the Advances in Neural Networks, 2008
2006
On-Line Nonlinear Process Monitoring Using Kernel Principal Component Analysis and Neural Network.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006
A New Method for Process Monitoring Based on Mixture Probabilistic Principal Component Analysis Models.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006
On-Line Batch Process Monitoring Using Multiway Kernel Independent Component Analysis.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006
2004
Chemical Separation Process Monitoring Based on Nonlinear Principal Component Analysis.
Proceedings of the Advances in Neural Networks, 2004