Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems
This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state o...
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| Published in | IEEE transactions on cybernetics Vol. 48; no. 6; pp. 1839 - 1848 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
IEEE
01.06.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions. |
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| AbstractList | This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions.This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions. This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions. |
| Author | Lin, Chong Zhang, Jing Chen, Bing Wang, Fang Meng, Xinzhu |
| Author_xml | – sequence: 1 givenname: Fang orcidid: 0000-0001-7729-5669 surname: Wang fullname: Wang, Fang email: sandywf75@126.com organization: College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China – sequence: 2 givenname: Bing orcidid: 0000-0002-0305-7411 surname: Chen fullname: Chen, Bing email: chenbing1958@126.com organization: Institute of Complexity Science, Qingdao University, Qingdao, China – sequence: 3 givenname: Chong surname: Lin fullname: Lin, Chong email: linchong2004@hotmail.com organization: Institute of Complexity Science, Qingdao University, Qingdao, China – sequence: 4 givenname: Jing surname: Zhang fullname: Zhang, Jing organization: Computer Science and Technology, Guangdong University of Foreign Studies, Guangzhou, China – sequence: 5 givenname: Xinzhu surname: Meng fullname: Meng, Xinzhu organization: College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28650838$$D View this record in MEDLINE/PubMed |
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| CODEN | ITCEB8 |
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| SubjectTerms | Adaptive control Adaptive neural control Adaptive systems Artificial neural networks Feedback control finite-time Neural networks Nonlinear control Nonlinear systems Output feedback Process controls quantized nonlinear systems Stability analysis Stability criteria State observers |
| Title | Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems |
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