Adaptive Event‐Triggered Output Feedback Consensus Tracking Control of Multi‐Agent Systems via K‐Filters

ABSTRACT

In this paper, the issue of adaptive event‐triggered output feedback consensus tracking dynamic surface control is discussed for nonlinear multi‐agent systems (MASs) with unmodeled dynamics. The system states are estimated via K‐filters. The unknown nonlinear continuous functions are approximated using radial basis function neural networks (RBFNNs). To lighten the load on communication, an event‐triggered control (ETC) method with a relative threshold is developed. By using command filter backstepping technology, a unique adaptive consensus tracking control strategy is presented. Then, through Lyapunov stability analysis, all signals in the closed‐loop system can be guaranteed to be semi‐globally uniformly ultimately bounded (SGUUB), and the Zeno phenomenon can be avoided. Finally, simulation results validate the effectiveness of the proposed method.