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Observer-Based Quasi-Synchronization of Delayed Dynamical Networks With Parameter Mismatch Under Impulsive Effect.
IEEE Transactions on Neural Networks and Learning Systems
|August 4, 2020
Summary
This study addresses quasi-synchronization in delayed dynamical networks with parameter mismatches and impulsive effects. A novel observer-based strategy ensures synchronization by estimating unknown states, proving effective through simulations.
Area of Science:
- Complex Systems and Networks
- Control Theory
- Dynamical Systems
Background:
- Observer-based control is crucial for systems with unmeasurable states.
- Delayed dynamical networks present challenges in synchronization due to time lags.
- Impulsive effects introduce discrete state changes, complicating system dynamics.
Purpose of the Study:
- To investigate the quasi-synchronization problem in delayed dynamical networks.
- To develop an observer-based control strategy for systems with parameter mismatch and impulsive effects.
- To ensure synchronization of slave nodes with a leader node despite system uncertainties.
Main Methods:
- A state estimation strategy is proposed to estimate unknown node states.
- A synchronization controller is designed based on the estimated states.
- Lyapunov function construction and Cauchy matrix analysis are employed to prove boundedness and stability.
Main Results:
- The proposed observer-based controller successfully achieves quasi-synchronization in the delayed dynamical network.
- The analysis confirms the boundedness of the system trajectory despite parameter mismatch and time-varying delays.
- Numerical simulations validate the effectiveness of the developed synchronization strategy.
Conclusions:
- The observer-based quasi-synchronization approach is effective for delayed dynamical networks with parameter mismatch and impulsive effects.
- The proposed method provides a robust framework for synchronizing complex network systems under challenging conditions.
- This research contributes to the advancement of control strategies for networked systems in practical applications.
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