Dynamics of an unmanned surface vehicle (USV) is usually hard to be modeled accurately due to system uncertainties and disturbances, which can significantly reduce system control performance. To guarantee a satisfied control performance under modeling uncertainties and disturbances, a novel control scheme combining adaptive fuzzy output regulation control and prescribed performance control is proposed in this paper. The unknown nonlinear dynamics of the USV is firstly approximated by a fuzzy logic system, and then an adaptive output regulation control law is developed using backstepping approach for the USV to track a reference system while rejecting disturbances and approximation errors induced by the fuzzy logic system. Meanwhile, the prescribed performance control technique is combined to the adaptive output regulation control design to reach a desired control performance in spite of the unknown system dynamics and disturbances. A simulation study is finally provided to demonstrate the effectiveness of the proposed approach.
Dynamics of an unmanned surface vehicle (USV) is usually hard to be modeled accurately due to system uncertainties and disturbances, which can significantly reduce system control performance. To guarantee a satisfied control performance under modeling uncertainties and disturbances, a novel control scheme combining adaptive fuzzy output regulation control and prescribed performance control is proposed in this paper. The unknown nonlinear dynamics of the USV is firstly approximated by a fuzzy logic system, and then an adaptive output regulation control law is developed using backstepping approach for the USV to track a reference system while rejecting disturbances and approximation errors induced by the fuzzy logic system. Meanwhile, the prescribed performance control technique is combined to the adaptive output regulation control design to reach a desired control performance in spite of the unknown system dynamics and disturbances. A simulation study is finally provided to demonstrate the effectiveness of the proposed approach.