BLSTM-Based Adaptive Finite-Time Output-Constrained Control for a Class of AUSs with Dynamic Disturbances and Actuator Faults Article Swipe
YOU?
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· 2021
· Open Access
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· DOI: https://doi.org/10.1155/2021/2221495
In this paper, a BLSTM-based adaptive finite-time control structure has been constructed for a class of aerospace unmanned systems (AUSs). Firstly, a novel neural network structure possessing both the time memory characteristics and high learning speed, broad long short-term memory (BLSTM) network, has been constructed. Secondly, several nonlinear functions are utilized to transform the tracking errors into a novel state vector to guarantee the output constraints of the AUSs. Thirdly, the fractional-order control law and the corresponding adaptive laws are designed, and as a result, the adaptive finite-time control scheme has been formed. Moreover, to handle the uncertainties and the faulty elevator outputs, an inequality of the multivariable systems is utilized. Consequently, by fusing the output of the BLSTM, the transformation of the tracking errors, and the adaptive finite-time control law, a novel BLSTM-based intelligent adaptive finite-time control structure has been established for the AUSs under output constraints. The simulation results show that the proposed BLSTM-based adaptive control algorithm can achieve favorable control results for the AUSs with multiple uncertainties.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.1155/2021/2221495
- https://downloads.hindawi.com/journals/mpe/2021/2221495.pdf
- OA Status
- hybrid
- Cited By
- 3
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3199719245
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3199719245Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1155/2021/2221495Digital Object Identifier
- Title
-
BLSTM-Based Adaptive Finite-Time Output-Constrained Control for a Class of AUSs with Dynamic Disturbances and Actuator FaultsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-09-23Full publication date if available
- Authors
-
Shiyi Huang, Lulu Rong, Xiaofei Chang, Zheng Wang, Zhaohui Yuan, Caisheng WeiList of authors in order
- Landing page
-
https://doi.org/10.1155/2021/2221495Publisher landing page
- PDF URL
-
https://downloads.hindawi.com/journals/mpe/2021/2221495.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://downloads.hindawi.com/journals/mpe/2021/2221495.pdfDirect OA link when available
- Concepts
-
Control theory (sociology), Computer science, Adaptive control, Transformation (genetics), Control (management), Actuator, Tracking (education), Artificial neural network, State (computer science), Algorithm, Artificial intelligence, Biochemistry, Gene, Pedagogy, Psychology, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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61Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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