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A Hybrid Switching Control Approach to Consensus of Multiagent Systems
IEEE Transactions on Cybernetics
|December 15, 2021
Summary
This study introduces a novel hybrid switching control (HSC) for multiagent systems (MASs), enhancing transient consensus performance. The new approach ensures continuous controller output and consistent signal direction for improved system stability.
Area of Science:
- Control Theory
- Systems Engineering
- Robotics
Background:
- Multiagent systems (MASs) require effective control strategies for coordinated behavior.
- Existing reset control methods for MAS consensus have limitations in transient performance.
- Developing advanced control techniques is crucial for improving the efficiency and stability of MAS.
Purpose of the Study:
- To develop a novel hybrid switching control (HSC) approach for multiagent systems (MASs).
- To enhance the transient consensus performance of MASs compared to existing reset control methods.
- To ensure continuous controller output and consistent signal direction for improved stability.
Main Methods:
- Introduction of a hybrid switched controller with two modes: reset control and gain control.
- Design of a switching mechanism to guarantee continuous controller output and same-sign input-output.
- Application of HSC to MAS consensus, proposing a protocol with proportional control and HSC.
- Construction of a closed-loop model using binary-value variables for Lyapunov-based analysis.
Main Results:
- The proposed HSC approach demonstrates superior transient consensus performance in MASs.
- The controller design ensures signal continuity and consistent sign, crucial for system stability.
- Lyapunov-based analysis confirms the effectiveness of the developed consensus protocol.
Conclusions:
- The novel hybrid switching control (HSC) approach significantly improves transient consensus in MASs.
- The controller's design guarantees essential properties for stable and efficient multiagent coordination.
- The findings provide a valuable advancement in control strategies for complex multiagent systems.
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