Handbook of Real-Time Computing pp 1-17 | Cite as

# Adaptive Consensus of Multiple Lagrangian Systems

## Abstract

Multi-agent systems have received a lot of attention in recent years due to their board applications in unmanned aerial vehicles, autonomous robots, and sensor networks. One important focus is the agent dynamics. Here, we focus on more realistic Lagrangian models, which can be used to represent a lot of physical systems. We study the leaderless consensus problem for multiple Lagrangian systems in the presence of parametric uncertainties under a general directed graph. We consider the cases with full relative information and without relative velocity information. In both cases, we first propose a control algorithm to make the agents achieve consensus. Then by introducing an integral term in the auxiliary variable design, we derive the final consensus equilibrium. We show that this equilibrium is dependent on the interactive topology and the initial positions of the agents. A Lyapunov-based method and the input-to-state stability theory are used for the convergence analysis.

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