Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints
This paper proposes an adaptive neural network (NN) control approach for a direct-current (DC) system with full state constraints. To guarantee that state constraints always remain in the asymmetric time-varying constraint regions, the asymmetric time-varying Barrier Lyapunov Function (BLF) is emplo...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/5082401 |
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| author | Lei Ma Dapeng Li |
| author_facet | Lei Ma Dapeng Li |
| author_sort | Lei Ma |
| collection | DOAJ |
| description | This paper proposes an adaptive neural network (NN) control approach for a direct-current (DC) system with full state constraints. To guarantee that state constraints always remain in the asymmetric time-varying constraint regions, the asymmetric time-varying Barrier Lyapunov Function (BLF) is employed to structure an adaptive NN controller. As we all know that the constant constraint is only a special case of the time-varying constraint, hence, the proposed control method is more general for dealing with constraint problem as compared with the existing works on DC systems. As far as we know, this system is the first studied situations with time-varying constraints. Using Lyapunov analysis, all signals in the closed-loop system are proved to be bounded and the constraints are not violated. In this paper, the effectiveness of the control method is demonstrated by simulation results. |
| format | Article |
| id | doaj-art-e7f71f2624e84edfad1b7f3af9189d6c |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e7f71f2624e84edfad1b7f3af9189d6c2025-02-03T06:12:04ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/50824015082401Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State ConstraintsLei Ma0Dapeng Li1College of Science, Liaoning University of Technology, Jinzhou, Liaoning 121001, ChinaSchool of Electrical Engineering, Liaoning University of Technology, Jinzhou 121001, ChinaThis paper proposes an adaptive neural network (NN) control approach for a direct-current (DC) system with full state constraints. To guarantee that state constraints always remain in the asymmetric time-varying constraint regions, the asymmetric time-varying Barrier Lyapunov Function (BLF) is employed to structure an adaptive NN controller. As we all know that the constant constraint is only a special case of the time-varying constraint, hence, the proposed control method is more general for dealing with constraint problem as compared with the existing works on DC systems. As far as we know, this system is the first studied situations with time-varying constraints. Using Lyapunov analysis, all signals in the closed-loop system are proved to be bounded and the constraints are not violated. In this paper, the effectiveness of the control method is demonstrated by simulation results.http://dx.doi.org/10.1155/2018/5082401 |
| spellingShingle | Lei Ma Dapeng Li Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints Complexity |
| title | Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints |
| title_full | Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints |
| title_fullStr | Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints |
| title_full_unstemmed | Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints |
| title_short | Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints |
| title_sort | adaptive neural networks control using barrier lyapunov functions for dc motor system with time varying state constraints |
| url | http://dx.doi.org/10.1155/2018/5082401 |
| work_keys_str_mv | AT leima adaptiveneuralnetworkscontrolusingbarrierlyapunovfunctionsfordcmotorsystemwithtimevaryingstateconstraints AT dapengli adaptiveneuralnetworkscontrolusingbarrierlyapunovfunctionsfordcmotorsystemwithtimevaryingstateconstraints |