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Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints
Joint Authors
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-18
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints.
In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem.
Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems.
Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized.
In order to achieve this goal, the time-varying barrier Lyapunov function (TVBLF) is used to prevent the states from violating time-varying constraints.
By the backstepping design, the adaptive controller will be obtained.
A radial basis function neural network (RBFNN) is used to estimate the uncertainties.
Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded.
The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness.
American Psychological Association (APA)
Lu, Shu-Min& Li, Dong-Juan. 2017. Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints. Complexity،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1143334
Modern Language Association (MLA)
Lu, Shu-Min& Li, Dong-Juan. Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints. Complexity No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1143334
American Medical Association (AMA)
Lu, Shu-Min& Li, Dong-Juan. Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints. Complexity. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1143334
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143334