Knowledge Management System Of Guangzhou Institute of Energy Conversion, CAS
基于BP神经网络整定的PID控制及其仿真 | |
Alternative Title | PID Controllers Based on BP Neural Networks and the Simulation |
高富强1; 李萍2; 张磊敏3; 曾令可4; 涂腾5; 刁浩明5 | |
2017-06 | |
Source Publication | 山东陶瓷 |
ISSN | 1005-0639 |
Volume | 40Issue:3Pages:27-31 |
Abstract | PID控制是连续系统控制理论中技术成熟、应用广泛的一种控制方法。但在实际应用中,其参数的整定往往是依靠经验和现场调试。本文把BP(Back Propagation)神经网络技术应用到PID控制中,利用其非线性函数逼近能力,对PID控制器进行整定,并通过仿真试验取得较好的结果。 |
Other Abstract | PID controllers are wildly used in cybernetics of continuous system, and the technique is ma- ture. But in practice, the tuning of PID parameters depends on experience and debug. In this paper, BPNN(Back Propagation Neural Network) technique was used to tune PID parameters because of its non--linear function capability. The simulation proves it is satisfactory. |
Keyword | PID 整定 BP神经网络 仿真 PID Tuning Back Propagation Neural Network Simulation |
DOI | 10.3969/j.issn.1005-0639.2017.03.007 |
Language | 中文 |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.giec.ac.cn/handle/344007/16587 |
Collection | 中国科学院广州能源研究所 |
Affiliation | 1.广州能源检测研究院,广州511447; 2.中国科学院广州能源研究所,广州510640; 3.江门出入境检验检疫局,江门529000; 4.华南理工大学,广州510640; 5.广州繁诺节能科技有限公司,广州510000 |
Recommended Citation GB/T 7714 | 高富强,李萍,张磊敏,等. 基于BP神经网络整定的PID控制及其仿真[J]. 山东陶瓷,2017,40(3):27-31. |
APA | 高富强,李萍,张磊敏,曾令可,涂腾,&刁浩明.(2017).基于BP神经网络整定的PID控制及其仿真.山东陶瓷,40(3),27-31. |
MLA | 高富强,et al."基于BP神经网络整定的PID控制及其仿真".山东陶瓷 40.3(2017):27-31. |
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