Sampled-Data Consensus Control With Distinct Input Delays and Switching Networks

In this paper, we develop a new delay compensation framework for solving consensus problems over a static directed graph, as well as dynamic graphs with joint connectedness. The idea is to employ the “nominal” control law designed for the delay-free case combined with the “approximate predictor-based” compensation of delays. The proposed control laws can achieve global consensus in the presence of arbitrarily long time delays, and no extra condition is introduced in comparison with the delay-free case. Numerical simulations are presented to validate the effectiveness of the proposed scheme.