Knowledge Commons of Institute of Automation，CAS
| Data-Driven Neuro-Optimal Temperature Control of Water-Gas Shift Reaction Using Stable Iterative Adaptive Dynamic Programming | |
Wei, Qinglai ; Liu, Derong; Derong Liu
| |
| 发表期刊 | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
 |
| 2014-11-01 | |
| 卷号 | 61期号:11页码:6399-6408 |
| 文章类型 | Article |
| 摘要 | In this paper, a novel data-driven stable iterative adaptive dynamic programming (ADP) algorithm is developed to solve optimal temperature control problems for water-gas shift (WGS) reaction systems. According to the system data, neural networks (NNs) are used to construct the dynamics of the WGS system and solve the reference control, respectively, where the mathematical model of the WGS system is unnecessary. Considering the reconstruction errors of NNs and the disturbances of the system and control input, a new stable iterative ADP algorithm is developed to obtain the optimal control law. The convergence property is developed to guarantee that the iterative performance index function converges to a finite neighborhood of the optimal performance index function. The stability property is developed to guarantee that each of the iterative control laws can make the tracking error uniformly ultimately bounded (UUB). NNs are developed to implement the stable iterative ADP algorithm. Finally, numerical results are given to illustrate the effectiveness of the developed method. |
| 关键词 | Adaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Approximation Errors Data-driven Control Neural Networks (Nns) Optimal Control Reinforcement Learning Water-gas Shift (Wgs) |
| WOS标题词 | Science & Technology ; Technology |
| 关键词[WOS] | TIME NONLINEAR-SYSTEMS ; CONTROL SCHEME ; FEEDBACK-CONTROL ; LEARNING CONTROL ; DESIGN ; ALGORITHM ; REINFORCEMENT ; CONVERTERS ; MODEL ; STATE |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Automation & Control Systems ; Engineering ; Instruments & Instrumentation |
| WOS类目 | Automation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation |
| WOS记录号 | WOS:000337123000062 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/3836 |
| 专题 | 多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队 |
| 通讯作者 | Derong Liu |
| 作者单位 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 第一作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Wei, Qinglai,Liu, Derong,Derong Liu. Data-Driven Neuro-Optimal Temperature Control of Water-Gas Shift Reaction Using Stable Iterative Adaptive Dynamic Programming[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2014,61(11):6399-6408. |
| APA | Wei, Qinglai,Liu, Derong,&Derong Liu.(2014).Data-Driven Neuro-Optimal Temperature Control of Water-Gas Shift Reaction Using Stable Iterative Adaptive Dynamic Programming.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,61(11),6399-6408. |
| MLA | Wei, Qinglai,et al."Data-Driven Neuro-Optimal Temperature Control of Water-Gas Shift Reaction Using Stable Iterative Adaptive Dynamic Programming".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 61.11(2014):6399-6408. |
| 条目包含的文件 | 下载所有文件 | |||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| 2014_TIE_Data-Driven（664KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
修改评论