Command filter-based adaptive neural two-bit-triggered containment control for saturated nonlinear multi-agent systems

Abstract

Abstract This paper considers the adaptive two-bit-triggered containment control problem for nonlinear multi-agent systems in the presence of input saturation. Since input saturation occurs frequently in practical systems, which can affect the stability of the multi-agent systems under consideration, an auxiliary design system is introduced to address this issue. Meanwhile, considering limited transmission resources in practical systems, this paper mainly focuses on the triggering condition and the control signal transmission bits, presenting a two-bit-triggered control approach to optimize the utilization of transmission resources. Furthermore, a command filter is introduced into the design process to solve the problem of complexity explosion. The proposed method ensures that all signals of the closed-loop system are bounded and the output signals of all followers converge to a convex hull spanned by the outputs of the leaders. Finally, two simulation examples are provided to verify the validity of the presented control scheme.