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Multi-agent dynamic formation interception control based on rigid graph
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AI
DOI：10.1007/s40747-024-01467-3.png)
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In this study, dynamic formation tracking and interception are performed by controlling multi-agent using a Euler-like Lagrangian model. The purpose is to use the distance-based rigid graph method to control multi-agent, and ultimately achieve dynamic formation tracking and target interception of multi-agent. Initially, distance-based graph stiffness and back-stepping techniques were considered to address the formation control challenge. This method helps achieve the initial expected formation and effectively complete the formation mission. Leaders continue to chase the moving target, while followers stick to the expected arrangement. The leader then precisely tracks the moving target and surrounds it within the formation. By using Lyapunov stability theory with adaptive control, it is ensured that the total distance meets finite and consistent error limits. Finally, the numerical simulation of the interception plan was carried out by 6 multi-agents and 1 target at different times to verify the effectiveness of the control method.
Keyword:
Dynamic formation tracking interception
Multi-agent
The distance-based rigid graph
Adaptive control
Euler-like Lagrangian Model
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4.6
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2.1K
被引数:
6.6K
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NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
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