Since the dynamics of autonomous underwater vehicles (AUVs) are highly nonlinear and their hydrodynamic coefficients vary with different operating conditions, a high performance control system of an AUV is needed to have the capacities of learning and adaptation to the variations of the AUV dynamics. In this paper, a linearly parameterized neural network is used to approximate the uncertainties of the vehicle dynamics, where the basis function vector of the network is constructed according to the vehicle physical properties. The proposed controller guarantees uniform boundedness of the vehicle trajectory tracking errors and network weights estimation errors based on the Lyapunov stability theory, where the network reconstruction errors and disturbances in the vehicle dynamics are bounded by an unknown constant. Numerical simulation studies are performed to illustrate the effectiveness of the proposed control scheme.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Neural net based nonlinear adaptive control for autonomous underwater vehicles


    Contributors:


    Publication date :

    2002


    Size :

    6 Seiten, 17 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Control of autonomous underwater vehicles using adaptive neural network

    Nguyen, Phung-Hung / Jung, Yun-Chul | Tema Archive | 2009




    Adaptive distributed formation control of multiple autonomous underwater vehicles

    Emrani, S. / Dirafzoon, A. / Talebi, H.A. | Tema Archive | 2011


    Autonomous underwater vehicles

    MCENTEE JARLATH / HAYES NATHANIAL / FIREBAUGH MILLARD | European Patent Office | 2024

    Free access