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Published on: May 8, 2021
Function projective synchronization of complex networks with asymmetric coupling via adaptive and pinning feedback
Lin Shi1, Hong Zhu1, Shouming Zhong2
1School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China.
This study explores function projective synchronization (FPS) in complex networks using hybrid control and asymmetric coupling. New criteria for achieving FPS were developed and validated through examples.
Area of Science:
- Complex Networks
- Control Theory
- Nonlinear Systems
Background:
- Function projective synchronization (FPS) is crucial for coordinating complex network dynamics.
- Existing research often assumes symmetric coupling matrices, limiting applicability.
- Investigating asymmetric coupling is essential for more realistic network models.
Purpose of the Study:
- To investigate function projective synchronization (FPS) in complex networks with asymmetric coupling matrices.
- To develop novel criteria for achieving FPS using hybrid control strategies.
- To demonstrate the effectiveness of the proposed methods through illustrative examples.
Main Methods:
- Utilizing hybrid control, combining adaptive and pinning feedback control.
- Developing new criteria for function projective synchronization under asymmetric coupling.
- Applying these methods to analyze synchronization in complex network models.
Main Results:
- New criteria for achieving function projective synchronization were successfully derived.
- The proposed hybrid control methods effectively addressed asymmetric coupling.
- Demonstrated the practical applicability and effectiveness of the developed criteria.
Conclusions:
- The proposed hybrid control approach effectively achieves function projective synchronization in complex networks with asymmetric coupling.
- The developed criteria offer a valuable tool for analyzing and controlling synchronization in complex systems.
- This work advances the understanding of synchronization dynamics in realistically coupled complex networks.
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