Consensus Control for Nonlinear Multiagent Systems with Sensor Faults

In this paper, the problem of consensus tracking control for a class of distributed nonlinear multiagent systems is studied. Considering the system with nonstrict-feedback structure and sensor faults, an adaptive neural network control scheme is proposed, which combines backstepping technique with radial basis function neural network. In the process of control design, neural network approximation technique and its structural characteristics are used to overcome the control design obstacles caused by unknown nonlinear function and nonstrict-feedback structure. A controller is constructed for the system considering the sensor faults, which can not only realize the consensus tracking control of the system, but also ensure that all signals of the closed-loop system are bounded. Finally, an example is given to show the effectiveness of the proposed scheme.