Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/62722
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dc.titleRobust learning control for robotic manipulators with an extension to a class of non-linear systems
dc.contributor.authorXu, J.-X.
dc.contributor.authorViswanathan, B.
dc.contributor.authorQu, Z.
dc.date.accessioned2014-06-17T06:54:09Z
dc.date.available2014-06-17T06:54:09Z
dc.date.issued2000-07-10
dc.identifier.citationXu, J.-X., Viswanathan, B., Qu, Z. (2000-07-10). Robust learning control for robotic manipulators with an extension to a class of non-linear systems. International Journal of Control 73 (10) : 858-870. ScholarBank@NUS Repository.
dc.identifier.issn00207179
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/62722
dc.description.abstractA 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 difficult 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/002071700405842
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleInternational Journal of Control
dc.description.volume73
dc.description.issue10
dc.description.page858-870
dc.description.codenIJCOA
dc.identifier.isiut000088562300006
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