Aiming at the model uncertainty,parameter perturbation and control input quantification problems in the formation control of underactuated unmanned surface vehicles(USVs)under complex marine environment,a sliding mode control algorithm of adaptive quantification neural network is proposed.In the USV dynamic subsystem,the guidance law based on the inner and outer loop control strategy is designed to solve the USV underactuated problem.Because the adopted dynamic model contains unknown terms and external environment interference,the radial basis function neural network is used to realize the estimation of interference in the USV dynamic subsystem.A linear analytical model is used to describe the input quantification process.The designed control system does not need the prior information of quantitative parameters.The system stability is proved based on the input-to-state stability theory.The effectiveness of the proposed algorithm is verified by the simulation experiment.
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