Robust learning control for robotic manipulators with an extension to a class of non-linear systems

    Authors

    J. X. Xu; B. Viswanathan;Z. H. Qu

    Abbreviated Journal Title

    Int. J. Control

    Keywords

    Automation & Control Systems

    Abstract

    A robust learning control (RLC) scheme is developed for robotic manipulators by a synthesis of learning control and robust control methods. The non-linear learning control strategy is applied directly to the structured system uncertainties that can be separated and expressed as products of unknown but repeatable (over iterations) state-independent time functions and known state-dependent functions. The non-linear uncertain terms in robotic dynamics such as centrifugal, Coriolis and gravitational forces belong to this category. For unstructured uncertainties which may have non-repeatable factors but are limited by a set of known bounding functions as the only a priori knowledge, e.g the frictions of a robotic manipulator, robust control strategies such as variable structure control strategy can be applied to ensure global asymptotic stability. By virtue of the learning and robust properties, the new control system can easily fulfil control objectives that are di? cult for either learning control or variable structure control alone to achieve satisfactorily. The proposed RLC scheme is further shown to be applicable to certain classes of non-linear uncertain systems which include robotic dynamics as a subset. Various important properties concerning learning control, such as the need for a resetting condition and derivative signals, whether using iterative control mode or repetitive control mode, are also made clear in relation to different control objectives and plant dynamics.

    Journal Title

    International Journal of Control

    Volume

    73

    Issue/Number

    10

    Publication Date

    1-1-2000

    Document Type

    Article

    Language

    English

    First Page

    858

    Last Page

    870

    WOS Identifier

    WOS:000088562300006

    ISSN

    0020-7179

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