基于大数据分析的PLC控制系统性能的优化与改进
Performance Optimization and Improvement of PLC Control System Based on Big Data Analysis
张瑞宽1
作者信息
- 1. 中国石油天然气股份有限公司大港油田分公司,天津 300280
- 折叠
摘要
为优化PLC控制系统的性能,提出了一种改进的Q-Learning强化学习算法.该算法在每次迭代优化过程中,利用模型预测未来的状态集,并在这些状态中选择了预期收益最大的决策.通过模拟实验,可发现该算法在控制相关的性能指标上具有明显优势.
Abstract
In order to optimize the performance of PLC control systems,this paper proposes an improved Q-Learning reinforcement learning algorithm.This algorithm utilizes the model to predict the future state set during each iterative optimization process,and selects the decision that maximizes the expected return among these states.Through simulation experiments,it can be seen that this algorithm has significant advantages in controlling related performance indicators.
关键词
强化学习/迭代优化/Q-Learning强化学习算法Key words
reinforcement learning/iterative optimization/Q-Learning reinforcement learning algorithm引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据