Hierarchical Robust Generalized Nash Equilibrium Seeking of High-Order Uncertain Nonlinear Systems.
IEEE Transactions on Cybernetics
|July 18, 2024
Summary
This study addresses distributed generalized Nash equilibrium (GNE) seeking in nonlinear multiagent systems (MASs) with complex constraints. A hierarchical approach ensures accurate GNE convergence despite disturbances.
Area of Science:
- Control Theory
- Game Theory
- Nonlinear Systems
Background:
- Generalized Nash Equilibrium (GNE) seeking is crucial for multiagent systems (MASs).
- Existing methods struggle with complex, coupled constraints in nonlinear MASs.
- High-order strict-feedback systems present unique control challenges.
Purpose of the Study:
- To develop a novel hierarchical approach for distributed GNE seeking.
- To address GNE seeking in high-order strict-feedback nonlinear MASs with general constraints.
- To ensure robust GNE convergence in the presence of nonvanishing disturbances.
Main Methods:
- A two-layer hierarchical GNE seeking strategy is proposed.
- A distributed primary-dual GNE estimator generates virtual reference signals.
- An adaptive tracking controller compensates for disturbances and output constraints.
Main Results:
- The proposed method successfully decouples GNE seeking into estimation and tracking layers.
- Virtual reference signals converge to the GNE under general constraints.
- Exact GNE seeking is achieved despite nonvanishing mismatched disturbances.
Conclusions:
- The hierarchical approach effectively solves the distributed GNE seeking problem for complex MASs.
- The method demonstrates robustness against disturbances.
- The findings offer a significant advancement in GNE seeking for nonlinear multiagent systems.
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