Abstract
Leader-follower consensus problem for multiagent systems (MASs) is an important research hotspot. However, the existing methods take the leader system matrix as a priori knowledge for each agent to design the controller and use the leader's state information. In fact, only the output information may be available in some practical applications. On this basis, this article first designs a novel adaptive distributed dynamic event-triggered observer for each follower to learn the minimum polynomial coefficients of the leader system matrix instead of the leader system matrix. The proposed method is scalable and suitable for large-scale MASs and can reduce the information transmission dimension in observer design. Then, an adaptive dynamic event-triggered compensator based on the observer and leader output information is designed for each follower, thereby solving the leader-follower consensus problem. Finally, several simulation examples are given to verify the effectiveness of the proposed scheme.
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