Design of ADET-DAT Algorithms over Directed Networks: An Extended-Dimensional Cooperative Technique

This article investigates an adaptive dynamic event-triggered (ADET) distributed average tracking (DAT) problem for multi-agent systems over directed communication networks. In practical scenarios, the asymmetry of directed communication networks often restricts bidirectional information exchange between agents, thereby affecting the implementation of DAT. To overcome this challenge, several ADET-DAT algorithms are developed in this article over directed communication networks. Compared with existing DAT algorithms, the proposed ADET-DAT algorithms have some breakthroughs. Firstly, over directed communication networks, the DAT problem is successfully solved by developing a distributed extended-dimensional estimator design methodology, which greatly expands the network structure of DAT algorithm's application. Then, by introducing a dynamic event-triggered (DET) communication mechanism, a class of DET-DAT algorithms may reduce the communication frequency in control processes. Further, by utilizing adaptive techniques, an ADET coupling strength is designed and embedded into the developed DAT algorithms, which eliminates the requirement for calculating Laplacian eigenvalues and reduces the communication frequency additionally. Finally, several cooperative tracking examples with multiple dynamic targets are provided to verify the effectiveness of the proposed algorithms.