Model-free learning control of neutralization processes using reinforcement learning-Reference-Cited by-同舟云学术

Model-free learning control of neutralization processes using reinforcement learning

Published:2007-09 Issue:6 Volume:20 Page:767-782
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Syafiie S.,Tadeo F.,Martinez E.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference27 articles.

1. Fuzzy self tuning PI control of pH in fermentation;Babuska;Journal of Engineering Application of Artificial Intelligence,2002

2. Fuzzy predictive control of highly nonlinearity pH process;Biasizzo;Computers and Chemical Engineering,1997

3. Applying neural networks to on-line updated PID controller for nonlinear process control;Chen;Journal of Process Control,2004

4. Dietterich, T.G., 1997. Hierarchical reinforcement learning with the MAXQ value function decomposition. Technical Report, Department of Computer Science, Oregon State University.

5. MIMO fuzzy internal model control;Edgar;Automatica,2000

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