@inproceedings{2b661486f38e46dc971dfff6e5eb9903,
title = "Model-Free Learning Control of a Nonlinear CSTR system",
abstract = "The control of two variables of a Nonlinear continuous stirred-tank reactor (CSTR) by the Model-Free Learning Control (MFLC) system is performed in this work. Firstly, it will show the model math of the plant. Secondly, it will design the MFLC System based on Reinforcement Learning (RL) approach, selecting the characteristics of the states, actions, rewards functions and other parameters of design. Finally, it will perform the simulations for step references, sinusoidal references and constant reference with disturbance signal.",
keywords = "action, algorithm, component, CSTR, engell, klatt, learning, learning. control, model-free, product, Q-learning, reactor, reinforcement, rewards, states, system, temperature",
author = "Leighton Estrada-Rayme and Paul Cardenas-Lizana",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 28th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021 ; Conference date: 05-08-2021 Through 07-08-2021",
year = "2021",
month = aug,
day = "5",
doi = "10.1109/INTERCON52678.2021.9532890",
language = "English",
series = "Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021",
}