Reinforcement Learning based Optimal Control for Constrained Nonlinear System via A Novel State-Dependent Transformation Article Swipe
Lei Yan
,
Zhi Liu
,
C. L. Philip Chen
,
Yun Zhang
,
Zongze Wu
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1066840/v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1066840/v1
This paper focus on developing an optimal controller for the strict-feedback nonlinear systems with or without asymmetric time-varying full state constraints. A novel nonlinear state-dependent transformation function is presented, by which the strict-feedback nonlinear systems with state constraints is transformed into a new strict-feedback where the state constraints is implicit in. Optimized backstepping technique is utilized to develop the optimal controller for the new strict-feedback system to track the desired reference signal without the feasibility conditions. Reinforcement learning (RL) is exploited to implement the optimal control in every step, where identifier, critic and action network are used to estimate the unknown system dynamics and generate the control output, respectively. It is theoretically proved that all the signals in the close loop system are bounded and the proposed optimal controller can track the desired signal with or without time-varying asymmetric full state constraints. Two simulation examples are presented demonstrating the efficacy of the proposed scheme.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-1066840/v1
- https://www.researchsquare.com/article/rs-1066840/latest.pdf
- OA Status
- green
- Cited By
- 1
- References
- 49
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3216449881
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- OpenAlex ID
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https://openalex.org/W3216449881Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-1066840/v1Digital Object Identifier
- Title
-
Reinforcement Learning based Optimal Control for Constrained Nonlinear System via A Novel State-Dependent TransformationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-11-22Full publication date if available
- Authors
-
Lei Yan, Zhi Liu, C. L. Philip Chen, Yun Zhang, Zongze WuList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-1066840/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-1066840/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-1066840/latest.pdfDirect OA link when available
- Concepts
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Reinforcement learning, Transformation (genetics), State (computer science), Nonlinear system, Computer science, Control (management), State dependent, Control theory (sociology), Artificial intelligence, Mathematics, Algorithm, Mathematical economics, Physics, Chemistry, Quantum mechanics, Biochemistry, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
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49Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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