Event-triggered adaptive consensus tracking control for non-affine multi-agent systems

Abstract

This paper presents the event-triggered consensus control problem for a class of multi-agent systems (MASs) in the non-affine form. An error-transformation-based design method is presented in the non-affine MASs. The radial basis function neural networks (RBFNNs) are used to approximate the unknown nonlinear functions. The dynamic surface control (DSC) technique is adopted to obtain parameters of the virtual controller through a first-order filter, which can make the calculation easier. An event-triggered control strategy is proposed to reduce communication frequency. Furthermore, it is further shown that the consensus tracking errors are semi-globally uniformly ultimately bounded (SGUUB). Finally, simulation results illustrate the effectiveness of the designed controller.