Model-Free Learning Control of Chemical Processes

S. SYAFIIE; F. TADEO; E. C. MARTÍNEZ

Reinforcement Learning: Theory and Applications

I-TECH Education and Publishing,

Lugar: Viena, Austria; Año: 2008; p. 295 - 311

Learning is the nature for human being. For example, a school-student learns a subject bydoing exercise and home-work. Then, a school-teacher grades the school-student’s works.From this student and teacher interaction, the ability of the student mastering the subject is afeedback that the previous teaching method is successful or failure. As a result, the teacherwill change the teaching method to improve the student ability for mastering the subject.This is a picture that the reinforcement learning (RL) agent learns the environment. This chapter is organized as follows: a MFLC algorithm for designing controller for chemicalprocess control is given in section 2. In section 3, the application for a simulated buffer tankcontrol is discussed. Laboratory online applications are discussed in section 4 for pH andORP control processes.