Robustness of a Class of Bias Update Controllers for Blending Systems

Author:

Alvarez-Ramirez Jose1,Morales America1,Suarez Rodolfo1

Affiliation:

1. Programa de Matematicas Aplicadas y Computacion, Instituto Mexicano del Petroleo, and Division de Ciencias Basicas e Ingenieria, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 Mexico

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A deep reinforcement learning approach to gasoline blending real-time optimization under uncertainty;Chinese Journal of Chemical Engineering;2024-07

2. Data driven fast real-time optimization with application to crude oil blending;2019 1st International Conference on Industrial Artificial Intelligence (IAI);2019-07

3. Modeling of Crude Oil Blending via Discrete-Time Neural Networks;Studies in Computational Intelligence;2010

4. NEURAL NETWORKS FOR THE OPTIMIZATION OF CRUDE OIL BLENDING;International Journal of Neural Systems;2005-10

5. Lyapunov-based optimizing control of nonlinear blending processes;IEEE Transactions on Control Systems Technology;2005-07

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