A distributed generalized Nash equilibrium seeking algorithm based on extremum seeking control Article Swipe
Feng Xiao
,
Xin Cai
,
Bo Wei
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2201.11003
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2201.11003
In this paper, a distributed non-model based seeking algorithm which combines the extremum seeking control (ESC) jointly with learning algorithms is proposed to seek a generalized Nash equilibrium (GNE) for a class of noncooperative games with coupled equality constraint. The strategy of each agent is restricted by both the coupled inter-agent constraint and local inequality constraints. Thanks to the ESC, it is unnecessary to know the specific expressions of agents' cost functions and local constraints and to know the strategies of other agents for the implementation of the proposed GNE seeking algorithm. To deal with the coupled constraints, only the Lagrange multiplier is transmitted among agents with some prior information about the coupled constraints. Moreover, a diminishing dither signal is designed in the seeking algorithm to remove undesirable steady-state oscillations. The non-local convergence of the designed seeking algorithm is analyzed via the singular perturbation theory, averaging analysis and Lyapunov stability theory. Numerical examples are given to verify the effectiveness of our proposed method.
Related Topics
Concepts
Mathematical optimization
Lagrange multiplier
Nash equilibrium
Constraint (computer-aided design)
Mathematics
Computer science
Lyapunov stability
Dither
Convergence (economics)
Class (philosophy)
Lyapunov function
Control theory (sociology)
Control (management)
Nonlinear system
Artificial intelligence
Physics
Geometry
Economic growth
Economics
Noise shaping
Quantum mechanics
Computer vision
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2201.11003
- https://arxiv.org/pdf/2201.11003
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4221138993
All OpenAlex metadata
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https://openalex.org/W4221138993Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2201.11003Digital Object Identifier
- Title
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A distributed generalized Nash equilibrium seeking algorithm based on extremum seeking controlWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-26Full publication date if available
- Authors
-
Feng Xiao, Xin Cai, Bo WeiList of authors in order
- Landing page
-
https://arxiv.org/abs/2201.11003Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2201.11003Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2201.11003Direct OA link when available
- Concepts
-
Mathematical optimization, Lagrange multiplier, Nash equilibrium, Constraint (computer-aided design), Mathematics, Computer science, Lyapunov stability, Dither, Convergence (economics), Class (philosophy), Lyapunov function, Control theory (sociology), Control (management), Nonlinear system, Artificial intelligence, Physics, Geometry, Economic growth, Economics, Noise shaping, Quantum mechanics, Computer visionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.examples | 152 |
| abstract_inverted_index.extremum | 12 |
| abstract_inverted_index.learning | 18 |
| abstract_inverted_index.proposed | 21, 88, 161 |
| abstract_inverted_index.singular | 142 |
| abstract_inverted_index.specific | 66 |
| abstract_inverted_index.strategy | 40 |
| abstract_inverted_index.Moreover, | 114 |
| abstract_inverted_index.Numerical | 151 |
| abstract_inverted_index.algorithm | 8, 124, 137 |
| abstract_inverted_index.averaging | 145 |
| abstract_inverted_index.functions | 71 |
| abstract_inverted_index.non-local | 131 |
| abstract_inverted_index.non-model | 5 |
| abstract_inverted_index.stability | 149 |
| abstract_inverted_index.algorithm. | 91 |
| abstract_inverted_index.algorithms | 19 |
| abstract_inverted_index.constraint | 51 |
| abstract_inverted_index.inequality | 54 |
| abstract_inverted_index.multiplier | 101 |
| abstract_inverted_index.restricted | 45 |
| abstract_inverted_index.strategies | 79 |
| abstract_inverted_index.constraint. | 38 |
| abstract_inverted_index.constraints | 74 |
| abstract_inverted_index.convergence | 132 |
| abstract_inverted_index.diminishing | 116 |
| abstract_inverted_index.distributed | 4 |
| abstract_inverted_index.equilibrium | 27 |
| abstract_inverted_index.expressions | 67 |
| abstract_inverted_index.generalized | 25 |
| abstract_inverted_index.information | 109 |
| abstract_inverted_index.inter-agent | 50 |
| abstract_inverted_index.transmitted | 103 |
| abstract_inverted_index.undesirable | 127 |
| abstract_inverted_index.unnecessary | 62 |
| abstract_inverted_index.constraints, | 97 |
| abstract_inverted_index.constraints. | 55, 113 |
| abstract_inverted_index.perturbation | 143 |
| abstract_inverted_index.steady-state | 128 |
| abstract_inverted_index.effectiveness | 158 |
| abstract_inverted_index.oscillations. | 129 |
| abstract_inverted_index.implementation | 85 |
| abstract_inverted_index.noncooperative | 33 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/10 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Reduced inequalities |
| citation_normalized_percentile.value | 0.02669693 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |