Adaptive NN Backstepping With Considering Integral of Tracking Error
In order to simplify the design procedure of traditional neural network backstepping and improve the robustness and precision of control, an improved scheme is studied for a class of nonlinear systems. To avoid reconstructing virtual control inputs in each recursive step, RBF neural networks are uti...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9123368/ |
| _version_ | 1819173431342530560 |
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| author | Jiangtao Xu Yu Fu Ganghui Cao Dewei Zhang Ya Yang |
| author_facet | Jiangtao Xu Yu Fu Ganghui Cao Dewei Zhang Ya Yang |
| author_sort | Jiangtao Xu |
| collection | DOAJ |
| description | In order to simplify the design procedure of traditional neural network backstepping and improve the robustness and precision of control, an improved scheme is studied for a class of nonlinear systems. To avoid reconstructing virtual control inputs in each recursive step, RBF neural networks are utilized as approximators to estimate the desired feedback control of the whole system only. Meanwhile, the integral action of tracking error is introduced into the backstepping design procedure, which not only participates in updating the neural network weight, but also serves as a component part of the control input. This design may benefit the parameter tuning and make controller perform better sometimes. Based on the Lyapunov synthesis approach, theoretical analysis and simulation results are provided to show the feasibility of the improved scheme. |
| first_indexed | 2024-12-22T20:22:58Z |
| format | Article |
| id | doaj.art-1c10427748ee45d7a48f61cdd0f51153 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T20:22:58Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1c10427748ee45d7a48f61cdd0f511532022-12-21T18:13:47ZengIEEEIEEE Access2169-35362020-01-01811543711544710.1109/ACCESS.2020.30044019123368Adaptive NN Backstepping With Considering Integral of Tracking ErrorJiangtao Xu0https://orcid.org/0000-0002-1144-1245Yu Fu1Ganghui Cao2https://orcid.org/0000-0001-9687-4754Dewei Zhang3Ya Yang4Department of Aerospace Engineering, Harbin Engineering University, Harbin, ChinaChina Academy of Launch Vehicle Technology, Beijing Institute of Astronautical Systems Engineering, Beijing, ChinaDepartment of Aerospace Engineering, Harbin Engineering University, Harbin, ChinaDepartment of Aerospace Engineering, Harbin Engineering University, Harbin, ChinaDepartment of Aerospace Engineering, Harbin Engineering University, Harbin, ChinaIn order to simplify the design procedure of traditional neural network backstepping and improve the robustness and precision of control, an improved scheme is studied for a class of nonlinear systems. To avoid reconstructing virtual control inputs in each recursive step, RBF neural networks are utilized as approximators to estimate the desired feedback control of the whole system only. Meanwhile, the integral action of tracking error is introduced into the backstepping design procedure, which not only participates in updating the neural network weight, but also serves as a component part of the control input. This design may benefit the parameter tuning and make controller perform better sometimes. Based on the Lyapunov synthesis approach, theoretical analysis and simulation results are provided to show the feasibility of the improved scheme.https://ieeexplore.ieee.org/document/9123368/Backsteppingadaptive nonlinear controlneural networks |
| spellingShingle | Jiangtao Xu Yu Fu Ganghui Cao Dewei Zhang Ya Yang Adaptive NN Backstepping With Considering Integral of Tracking Error IEEE Access Backstepping adaptive nonlinear control neural networks |
| title | Adaptive NN Backstepping With Considering Integral of Tracking Error |
| title_full | Adaptive NN Backstepping With Considering Integral of Tracking Error |
| title_fullStr | Adaptive NN Backstepping With Considering Integral of Tracking Error |
| title_full_unstemmed | Adaptive NN Backstepping With Considering Integral of Tracking Error |
| title_short | Adaptive NN Backstepping With Considering Integral of Tracking Error |
| title_sort | adaptive nn backstepping with considering integral of tracking error |
| topic | Backstepping adaptive nonlinear control neural networks |
| url | https://ieeexplore.ieee.org/document/9123368/ |
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