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Coordination of multiple agents with double-integrator dynamics under generalized interaction topologies
Jiahu Qin1, Wei Xing Zheng, Huijun Gao
1Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, China. jiahu.qin@anu.edu.au
Summary
This paper studies consensus strategies for multi-agent systems with double-integrator dynamics. It establishes conditions for consensus under various network topologies, including fixed and dynamic ones, offering more relaxed criteria for dynamic networks.
Area of Science:
- Control Theory
- Robotics
- Networked Systems
Background:
- Multi-agent systems require coordinated behavior for tasks.
- Consensus algorithms enable agents to agree on a common value.
- Double-integrator dynamics are common in modeling physical systems.
Purpose of the Study:
- To investigate consensus convergence for multi-agent systems with double-integrator dynamics.
- To analyze consensus under different network topology configurations.
- To develop and verify conditions for achieving consensus in fixed and dynamic networks.
Main Methods:
- Analysis of consensus strategies under distinct graph structures for position and velocity information.
- Systematic investigation of consensus algorithms for fixed and time-varying directed interaction topologies.
- Derivation of sufficient conditions for consensus in different settings.
- Establishment of necessary and sufficient conditions for fixed topologies.
Main Results:
- Sufficient conditions for consensus are derived when position and velocity information flows use different graphs.
- A necessary and sufficient condition for average consensus is established for fixed, identical graph topologies.
- Relaxed sufficient conditions for consensus are obtained for dynamically changing topologies.
Conclusions:
- The study provides theoretical guarantees for consensus achievement in multi-agent systems.
- The findings offer more flexible conditions for consensus in dynamic network environments.
- Numerical examples validate the effectiveness of the derived theoretical results.
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