This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles(UUVs)with unknown dead-zone inputs.The primary objective is to design an adaptive trajectory tracking error constraint cont...This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles(UUVs)with unknown dead-zone inputs.The primary objective is to design an adaptive trajectory tracking error constraint controller using the fully actuated systems(FAs)approach to enable UUVs to asymptotically track target signals.Firstly,a novel error constraint fully actuated systems(ECFAs)approach is proposed by incorporating the tracking error dependent normalized function and barrier function along with time-varying scaling.Secondly,in order to deal with the model uncertainties of the UUVs,adaptive radial basis function neural networks(RBFNNs)is combined with the ECFAs approach.Then,a positive time-varying integral function is introduced to completely eliminate the effect of the residual effect caused by unknown dead-zone inputs,and it is proved that the trajectory tracking error converges to zero asymptotically based on the Lyapunov functions.Finally,the simulation results demonstrate the effectiveness of the designed adaptive controller.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62273297,62103353,61825304,and 6182500417in part by the Innovative Research Groups of the Natural Science Foundation of Hebei Province under Grant No.E2020203174+2 种基金in part by Hebei Innovation Capability Improvement Plan Project under Grant No.22567619Hin part by Youth Top Talent Project of Hebei Province under Grant No.HY2024050021in part by Post-graduate Innovation Fund Project of Hebei Province under Grant No.CXZZSS2023042。
文摘This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles(UUVs)with unknown dead-zone inputs.The primary objective is to design an adaptive trajectory tracking error constraint controller using the fully actuated systems(FAs)approach to enable UUVs to asymptotically track target signals.Firstly,a novel error constraint fully actuated systems(ECFAs)approach is proposed by incorporating the tracking error dependent normalized function and barrier function along with time-varying scaling.Secondly,in order to deal with the model uncertainties of the UUVs,adaptive radial basis function neural networks(RBFNNs)is combined with the ECFAs approach.Then,a positive time-varying integral function is introduced to completely eliminate the effect of the residual effect caused by unknown dead-zone inputs,and it is proved that the trajectory tracking error converges to zero asymptotically based on the Lyapunov functions.Finally,the simulation results demonstrate the effectiveness of the designed adaptive controller.
