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Updated: May 8, 2025
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Co-evolutionary control of a class of coupled mixed-feedback systems
Luis Guillermo Venegas-Pineda1, Hildeberto Jardón-Kojakhmetov1, Ming Cao2
1Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Nijenborgh 9, 9747AG Groningen, The Netherlands.
Chaos (Woodbury, N.Y.)
|March 25, 2025
Summary
This study introduces novel control strategies to stabilize desired oscillatory patterns in networked systems without altering their dynamics. Two adaptive methods are presented, one requiring full system knowledge and the other using local error information.
Area of Science:
- Complex Systems
- Control Theory
- Network Science
Background:
- Oscillatory behavior is common in natural and engineered systems.
- Self-regulating mechanisms often drive these oscillations.
- Stabilizing specific oscillatory patterns in existing networks is challenging.
Purpose of the Study:
- To develop control strategies for stabilizing desired oscillatory patterns in networked systems.
- To address the constraint of not altering internal dynamics or interconnections.
- To propose adaptive control rules for network edges.
Main Methods:
- Proposed two distinct control strategies: one with full system knowledge, one with local error information.
- Implemented controllers as co-evolutionary, adaptive rules on network edges.
- Validated the approach in scenarios like synchronization and time-varying networks.
Main Results:
- Demonstrated the ability to stabilize desired oscillatory patterns.
- Showcased the effectiveness of both full knowledge and local error-based control.
- Validated adaptability in dynamic network structures.
Conclusions:
- The proposed adaptive control strategies effectively stabilize desired oscillatory patterns in networked systems.
- The methods are versatile, applicable with varying levels of system information.
- The approach is robust to changes in network structure.
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