| Neural Dynamics for Control of Industrial Agitator Tank With Rapid Convergence and Perturbations Rejection | |
| Duan, Wenhui1,4; Xiao, Xiuchun2; Fu, Dongyang2; Yan, Jingwen3; Liu, Mei1; Zhang, Jiliang1; Jin, Long1,4 | |
| Source Publication | IEEE ACCESS
 |
| ISSN | 2169-3536 |
| 2019 | |
| Volume | 7Pages:102941-102950 |
| Corresponding Author | Xiao, Xiuchun(xcxiao@hotmail.com) ; Yan, Jingwen(jwyan@stu.edu.cn) |
| Abstract | The industrial agitator tank is a widely used equipment in the chemical industry for the production of the chemical reagents. The high-performance agitator tank controller is critical to increase its productivity. In this paper, we propose an agitator tank controller based on a neural dynamics method with a shorter error-converging time in comparison with the existing methods. In addition, the controller also has a strong capability to reject perturbations. Furthermore, the superiority of the proposed agitator tank controller is theoretically analyzed. Ultimately, computer simulations synthesized by the proposed agitator tank controller are conducted. The numerical results validate the superior performance of the proposed controller. |
| Keyword | Chemical industry automatic control control design neural dynamics method rapid convergence perturbations rejection |
| DOI | 10.1109/ACCESS.2019.2930323 |
| WOS Keyword | CHEMICAL REAGENTS ; MIXING TIME ; NETWORK ; SYSTEMS ; SIMULATIONS |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[61703189] ; International Science and Technology Cooperation Program of China[2017YFE0118900] ; Key Laboratory of Digital Signal and Image Processing of Guangdong Province[2016GDDSIPL-02] ; Doctoral Initiating Project of Guangdong Ocean University[E13428] ; Innovation and Strength Project of Guangdong Ocean University[Q15090] ; Innovation and Strength Project of Guangdong Ocean University[230419065] ; Natural Science Foundation of Gansu Province, China[18JR3RA264] ; Sichuan Science and Technology Program[19YYJC1656] ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences[20190112] ; Fundamental Research Funds for the Central Universities[lzujbky-2019-89] ; National Natural Science Foundation of China[61703189] ; International Science and Technology Cooperation Program of China[2017YFE0118900] ; Key Laboratory of Digital Signal and Image Processing of Guangdong Province[2016GDDSIPL-02] ; Doctoral Initiating Project of Guangdong Ocean University[E13428] ; Innovation and Strength Project of Guangdong Ocean University[Q15090] ; Innovation and Strength Project of Guangdong Ocean University[230419065] ; Natural Science Foundation of Gansu Province, China[18JR3RA264] ; Sichuan Science and Technology Program[19YYJC1656] ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences[20190112] ; Fundamental Research Funds for the Central Universities[lzujbky-2019-89] |
| Funding Organization | National Natural Science Foundation of China ; International Science and Technology Cooperation Program of China ; Key Laboratory of Digital Signal and Image Processing of Guangdong Province ; Doctoral Initiating Project of Guangdong Ocean University ; Innovation and Strength Project of Guangdong Ocean University ; Natural Science Foundation of Gansu Province, China ; Sichuan Science and Technology Program ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences ; Fundamental Research Funds for the Central Universities |
| WOS Research Area | Computer Science ; Engineering ; Telecommunications |
| WOS Subject | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications |
| WOS ID | WOS:000481688500206 |
| Publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/27605 |
| Collection | 复杂系统管理与控制国家重点实验室_先进机器人 |
| Corresponding Author | Xiao, Xiuchun; Yan, Jingwen |
| Affiliation | 1.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Gansu, Peoples R China 2.Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Peoples R China 3.Shantou Univ, Coll Engn, Shantou 515063, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| First Author Affilication | Institute of Automation, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Duan, Wenhui,Xiao, Xiuchun,Fu, Dongyang,et al. Neural Dynamics for Control of Industrial Agitator Tank With Rapid Convergence and Perturbations Rejection[J]. IEEE ACCESS,2019,7:102941-102950. |
| APA | Duan, Wenhui.,Xiao, Xiuchun.,Fu, Dongyang.,Yan, Jingwen.,Liu, Mei.,...&Jin, Long.(2019).Neural Dynamics for Control of Industrial Agitator Tank With Rapid Convergence and Perturbations Rejection.IEEE ACCESS,7,102941-102950. |
| MLA | Duan, Wenhui,et al."Neural Dynamics for Control of Industrial Agitator Tank With Rapid Convergence and Perturbations Rejection".IEEE ACCESS 7(2019):102941-102950. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment