Abstract
This paper studies the adaptive group consensus problem of networked mechanical systems formulated by Lagrangian dynamics under directed acyclic network topology by the use of adaptive control scheme based on neural networks. A distributed group consensus algorithm is proposed for such networked mechanical systems with communication delays, and then a simple yet generic criterion on the convergence for such algorithm over directed acyclic topology is established. Furthermore, the effect of time delays on the performance of adaptive group consensus are numerically investigated. It is shown that the networked mechanical systems with communication delays can always reach the group consensus if each subgroup has a directed spanning tree. Subsequently, numerical examples illustrate and visualize the effectiveness and feasibility of the theoretical results.
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