Adaptive cooperative dynamic surface control of non-strict feedback multi-agent systems with input dead-zones and actuator failures

Abstract

This paper discusses the consensus tracking problem for a class of nonlinear multi-agent systems (MASs) with output constraints, unmodeled dynamics, nonsymmetric input dead-zones and actuator failures under directed graphs, and proposes an adaptive cooperative neural dynamic surface control (DSC) strategy. Using the properties of invertible nonlinear mapping and Gaussian function, output constraints and non-strict feedback terms are separately dealt with. A measurable dynamic signal produced by an auxiliary first-order system is used to eliminate the influence of unmodeled dynamics on the system. Two input models of input dead-zone and actuator failure are linearized, each follower control signal is constructed via DSC. All the signals of the closed-loop system are proved to be cooperative semi-globally uniformly ultimately bounded, and all the followers can accomplish a desired consensus results. Finally, the simulation results are provided to illustrate the availability of the presented adaptive control approach.