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Generalized Distributed Optimal Coordination for Multiagent Systems via Weak Coupling Hierarchical Control Framework
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AI
DOI：10.1109/TASE.2024.3492018.png)
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摘要
En 中文
In this article, we reformulate the distributed optimal coordination problem for multi-agent systems to broaden its applicability across a wider range of coordination scenarios, thereby introducing a Generalized Distributed Optimal Coordination (GDOC) problem. In GDOC, the inter-agent relationships evolve from equality (consensus) to affinity (coordination), while local cost functions are unified as blends of parameters and shared basis functions, enabling cohesive network optimization. To address the GDOC problem, we propose a weak coupling hierarchical control framework for heterogeneous multi-agent systems. This framework consists of three layers: a signal generator, a tracking controller, and a speed regulator. For the generator, a transformed consensus protocol is designed for agents to estimate the global cost function and feasible set in a distributed manner, with the gradient projection method applied to minimize the objective function locally. For the controller, an observer-based output feedback control law is designed through system decomposition. For the regulator, a dynamic adaptive parameter is introduced to adjust the updating speed of the reference signal based on the agent's relative tracking ability. The proposed framework not only preserves the universality of hierarchical control but also addresses the limitation of topdown structural open-loop control by introducing a regulator to form a bottom-up feedback loop. Finally, the effectiveness of the proposed framework is verified by Lyapunov stability theory analysis and simulation experiments.
Keyword:
Cost function
Couplings
Vectors
Multi-agent systems
Generators
Control systems
Regulators
Signal generators
Feedback loop
Complexity theory
Distributed optimal coordination
hierarchical control
weak coupling
multi-agent system
期刊
IF:
6.4
论文数:
5.1K
被引数:
1.6W
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