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Consensus of Stochastic Dynamical Multiagent Systems in Directed Networks via PI Protocols
Summary
This study addresses mean square consensus for nonlinear multiagent systems (MASs) using proportional-integral (PI) protocols. New conditions ensure consensus in directed networks, bridging theory and practice.
Area of Science:
- Control Theory
- Swarm Intelligence
- Networked Systems
Background:
- Multiagent systems (MASs) are crucial for swarm intelligence applications.
- A gap exists between theoretical control strategies and practical engineering for MASs.
- Achieving consensus in stochastic nonlinear MASs within directed networks is challenging.
Purpose of the Study:
- To solve mean square consensus problems for stochastic dynamical nonlinear MASs.
- To design and analyze proportional-integral (PI) control protocols for directed networks.
- To bridge the gap between control theory and engineering practices in MASs.
Main Methods:
- Utilizing general algebraic connectivity for strongly connected networks.
- Employing M-matrix approaches for networks with a spanning tree.
- Constructing Lyapunov functions and applying stochastic analysis techniques.
- Leveraging LaSalle's invariant principles for stability analysis.
Main Results:
- Sufficient conditions for achieving mean square consensus in directed networks are derived.
- The effectiveness of PI protocols is demonstrated for stochastic dynamical nonlinear MASs.
- Consensus is achieved under specific network topologies and system dynamics.
Conclusions:
- The proposed PI protocols and derived conditions effectively enable mean square consensus.
- The findings contribute to practical applications of swarm intelligence and MAS control.
- This research validates theoretical approaches through numerical simulations.
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