An Implicit Function-Based Adaptive Control Scheme for Noncanonical-Form Discrete-Time Neural-Network Systems
文献类型：期刊论文
| 作者 | Zhang, Yanjun1,2; Tao, Gang3; Chen, Mou4; Chen, Wen5; Zhang, Zhengqiang1 |
| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
 |
| 出版日期 | 2021-12-01 |
| 卷号 | 51期号:12页码:5728-5739 |
| 关键词 | Adaptive control Uncertainty Nonlinear systems Adaptation models Asymptotic stability Stability analysis Adaptive control asymptotic output tracking discrete time (DT) implicit function noncanonical form |
| ISSN号 | 2168-2267 |
| DOI | 10.1109/TCYB.2019.2958844 |
| 英文摘要 | This article proposes a new implicit function-based adaptive control scheme for the discrete-time neural-network systems in a general noncanonical form. Feedback linearization for such systems leads to the output dynamics nonlinear dependence on the system states, the control input, and uncertain parameters, which leads to the nonlinear parametrization problem, the implicit relative degree problem, and the difficulty to specify an analytical adaptive controller. To address these problems, we first develop a new adaptive parameter estimation strategy to deal with all uncertain parameters, especially, those of nonlinearly parameterized forms, in the output dynamics. Then, we construct a key implicit function equation using available signals and parameter estimates. By solving the equation, a unique adaptive control law is derived to ensure asymptotic output tracking and closed-loop stability. Alternatively, we design an iterative solution-based adaptive control law which is easy to implement and ensure output tracking and closed-loop stability. The simulation study is given to demonstrate the design procedure and verify the effectiveness of the proposed adaptive control scheme. |
| 资助项目 | National Key R&D Program of China[2018YFA0703800] ; National Natural Science Foundation of China[61803226] ; National Natural Science Foundation of China[61533009] ; National Natural Science Foundation of China[61873330] ; National Natural Science Foundation of China[61877057] ; Taishan Scholarship Project of Shandong Province[tsqn20161032] |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000733232400012 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/59784]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Zhang, Zhengqiang |
| 作者单位 | 1.Qufu Normal Univ, Sch Engn, Qufu 273165, Shandong, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China 3.Univ Virginia, Dept Elect & Comp Engn, Charlottesville, VA 22903 USA 4.Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Peoples R China 5.Wayne State Univ, Div Engn Technol, Detroit, MI 48201 USA |
| 推荐引用方式 GB/T 7714 | Zhang, Yanjun,Tao, Gang,Chen, Mou,et al. An Implicit Function-Based Adaptive Control Scheme for Noncanonical-Form Discrete-Time Neural-Network Systems[J]. IEEE TRANSACTIONS ON CYBERNETICS,2021,51(12):5728-5739. |
| APA | Zhang, Yanjun,Tao, Gang,Chen, Mou,Chen, Wen,&Zhang, Zhengqiang.(2021).An Implicit Function-Based Adaptive Control Scheme for Noncanonical-Form Discrete-Time Neural-Network Systems.IEEE TRANSACTIONS ON CYBERNETICS,51(12),5728-5739. |
| MLA | Zhang, Yanjun,et al."An Implicit Function-Based Adaptive Control Scheme for Noncanonical-Form Discrete-Time Neural-Network Systems".IEEE TRANSACTIONS ON CYBERNETICS 51.12(2021):5728-5739. |
入库方式： OAI收割
来源：数学与系统科学研究院
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