Data‐driven adaptive resilient funnel consensus tracking of multiagent systems under jamming attacks

Abstract

In this article, we investigate a model‐free adaptive funnel control framework for nonlinear multiagent systems under jamming attacks. An equivalent time‐varying linear data model is built for agents by utilizing the dynamic linearization approach. Then, a predefined funnel function is presented such that the tracking errors are expected to evolve within a predetermined range. The transient and steady‐state behaviors of the tracking error can be improved by adjusting the parameter values of the funnel function. Moreover, the Stackelberg game is employed to determine the optimal transmission power between the transmitters and jammers considering the state of the transmission channel, which influences the jamming attack rate. Based on funnel control, a model‐free adaptive funnel control scheme is presented to guarantee that the tracking error remains within a funnel boundary (even in the presence of jamming attacks) and the transient and steady‐state performances are improved. The effectiveness of the proposed algorithm is further demonstrated through simulations.