Adaptive Intelligent Output Feedback Consensus Control for Nonlinear Multiagent Systems With Switched Topologies and Dead-Zone

This article studies the neural network (NN) adaptive consensus control issue for nonlinear multiagent systems (MASs) with dead-zone (DZ) output and jointly connected topologies. NNs are utilized to identify unknown agents, and a state observer is established to handle the problem resulted from unmeasurable states. A smooth inverse model is designed to replace nonsmooth DZ such that the nonsmooth problem of the system output is avoided. To estimate the unknown leader and its high-order derivatives under jointly connected topologies, a distributed observer is constructed. By using backstepping control technique, an output feedback consensus control scheme is established. It is demonstrated that all the variables of the controlled MASs are bounded despite of DZ output, and the followers can track the trajectory of the leader. Furthermore, multiple unmanned surface vehicles (USVs) are given to verify the feasibility of the presented consensus control methodology.