Adaptive neural output feedback control for stochastic nonlinear time-delay systems with unknown control directions
This paper first focuses on the problem of adaptive output feedback stabilization for a more general class of stochastic nonlinear time-delay systems with unknown control directions. By using a linear state transformation, the original system is transformed to a new system for which control design b...
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Published in | Neural computing & applications Vol. 25; no. 7-8; pp. 1979 - 1992 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
London
Springer London
01.12.2014
Springer |
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Abstract | This paper first focuses on the problem of adaptive output feedback stabilization for a more general class of stochastic nonlinear time-delay systems with unknown control directions. By using a linear state transformation, the original system is transformed to a new system for which control design becomes feasible. Then a novel adaptive neural network (NN) output feedback control strategy, which only contains one adaptive parameter, is developed for such systems by combining the input-driven filter design, the backstepping technique, the NN’s parameterization, the Nussbaum gain function method and the Lyapunov–Krasovskii approach. The proposed control design guarantees that all signals in the closed-loop systems are 4-moment (or 2-moment) semi-globally uniformly bounded. Finally, two simulation examples are given to demonstrate the effectiveness and the applicability of the proposed control design. |
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AbstractList | This paper first focuses on the problem of adaptive output feedback stabilization for a more general class of stochastic nonlinear time-delay systems with unknown control directions. By using a linear state transformation, the original system is transformed to a new system for which control design becomes feasible. Then a novel adaptive neural network (NN) output feedback control strategy, which only contains one adaptive parameter, is developed for such systems by combining the input-driven filter design, the backstepping technique, the NN’s parameterization, the Nussbaum gain function method and the Lyapunov–Krasovskii approach. The proposed control design guarantees that all signals in the closed-loop systems are 4-moment (or 2-moment) semi-globally uniformly bounded. Finally, two simulation examples are given to demonstrate the effectiveness and the applicability of the proposed control design. |
Author | Yu, Zhaoxu Li, Shugang Du, Hongbin |
Author_xml | – sequence: 1 givenname: Zhaoxu surname: Yu fullname: Yu, Zhaoxu email: yyzx@ecust.edu.cn organization: Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education, East China University of Science and Technology – sequence: 2 givenname: Shugang surname: Li fullname: Li, Shugang organization: Department of Industrial Engineering and Logistics, Shanghai Jiao Tong University – sequence: 3 givenname: Hongbin surname: Du fullname: Du, Hongbin organization: Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education, East China University of Science and Technology |
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CitedBy_id | crossref_primary_10_1007_s00521_015_1855_6 crossref_primary_10_1080_00207721_2020_1837993 crossref_primary_10_1016_j_neucom_2017_12_023 crossref_primary_10_1155_2015_723425 crossref_primary_10_1016_j_eswa_2022_116627 crossref_primary_10_1049_cth2_12221 crossref_primary_10_1007_s00521_017_3180_8 crossref_primary_10_1007_s11071_021_06456_6 crossref_primary_10_1007_s00521_019_04204_x crossref_primary_10_1109_TNNLS_2017_2669088 crossref_primary_10_1016_j_jfranklin_2019_12_011 crossref_primary_10_1109_TSMC_2023_3298923 |
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Keywords | Unknown control direction Neural network Time-varying delay Stochastic nonlinear systems Output feedback Non linear control Delay control Feedback regulation Control synthesis Parameterization Adaptive control Adaptive method Stochastic system Time varying system Uncertain system Delay time Closed loop Delay system Non linear system Recursive algorithm Backstepping control Closed feedback Neurocontrollers Linear system Linear transformation Lyapunov function Payoff function |
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Snippet | This paper first focuses on the problem of adaptive output feedback stabilization for a more general class of stochastic nonlinear time-delay systems with... |
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SubjectTerms | Adaptative systems Applied sciences Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer science; control theory; systems Control system analysis Control system synthesis Control theory. Systems Data Mining and Knowledge Discovery Exact sciences and technology Image Processing and Computer Vision Modelling and identification Original Article Probability and Statistics in Computer Science |
Title | Adaptive neural output feedback control for stochastic nonlinear time-delay systems with unknown control directions |
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