Robust adaptive control of a class of nonlinearly parameterised time-varying uncertain systems

    Authors

    J. Wang;Z. Qu

    Comments

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    Abbreviated Journal Title

    IET Contr. Theory Appl.

    Keywords

    NEURAL-CONTROL; DESIGN; NETWORKS; TRACKING; SCHEME; PLANTS; Automation & Control Systems; Engineering, Electrical & Electronic; Instruments & Instrumentation

    Abstract

    A robust adaptive control is presented for a class of time-varying nonlinear uncertain systems which have a fractional nonlinearly parameterised structure. The proposed design is based on robust adaptive backstepping and neural network approximation. The unknown time-varying parameters in the fractional nonlinear functions are estimated using a smooth projection algorithm and estimation errors are robustly compensated for by the additive terms in the proposed virtual and actual controls. Neural networks are employed to approximate the completely unknown bounding functions of the disturbance terms, and their weights as well as approximation errors are adaptively tuned. It is proved that the proposed robust adaptive control can ensure the semi-global uniform ultimate boundedness of all the closed-loop system signals. The control performance can be improved by an appropriate choice of the design parameters. Simulation results are provided to verify the effectiveness of the proposed design.

    Journal Title

    Iet Control Theory and Applications

    Volume

    3

    Issue/Number

    6

    Publication Date

    1-1-2009

    Document Type

    Article

    Language

    English

    First Page

    617

    Last Page

    630

    WOS Identifier

    WOS:000266275600002

    ISSN

    1751-8644

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