|Table of Contents|

Optimization of Process Parameters of Rotary Kiln Based on Model-Based Reinforcement Learning Under the Dual Objectives of Coal and Electricity(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2023年01期
Page:
75-83
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
Optimization of Process Parameters of Rotary Kiln Based on Model-Based Reinforcement Learning Under the Dual Objectives of Coal and Electricity
Author(s):
Zhang Xiang1; Xie Tian1; Cao Jian1; Zhu Yi2
(1.Luculent Smart Technology Co.,Ltd,Nanjing 210005,China) (2.College of Information Engineering,Yangzhou University,Yangzhou 225000,China)
Keywords:
rotary kiln; process parameter optimization; probabilistic neural network; model-based offline strategy optimization; coal-electricity dual objective
PACS:
TP181
DOI:
10.3969/j.issn.1672-1292.2023.01.010
Abstract:
Aiming at the optimization problem of rotary kiln process parameters under the dual objectives of coal and electricity, this paper proposes a model-based reinforcement learning solution. Firstly, data processing and aggregation were performed on historical process parameters and operating targets in units of fixed time intervals. Secondly, a probabilistic neural network is built to establish the relationship model between the control parameters of the rotary kiln, the influencing parameters, and the operating target value, which was used as the reward model in the later reinforcement learning framework. Then, a reinforcement learning algorithm based on model-based offline strategy optimization was used to construct a control parameter recommendation agent, and at the same time, the coal and electricity consumption of the rotary kiln production process was optimized. Finally, a case analysis was given to prove the adaptability and high efficiency of the proposed method for optimizing the process parameters of rotary kiln.

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Last Update: 2023-03-15