Please use this identifier to cite or link to this item: https://doi.org/10.1109/IROS.2012.6386257
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dc.titleAdaptive control for robot manipulators under ellipsoidal task space constraints
dc.contributor.authorTee, K.P.
dc.contributor.authorGe, S.S.
dc.contributor.authorYan, R.
dc.contributor.authorLi, H.
dc.date.accessioned2014-10-07T04:41:14Z
dc.date.available2014-10-07T04:41:14Z
dc.date.issued2012
dc.identifier.citationTee, K.P.,Ge, S.S.,Yan, R.,Li, H. (2012). Adaptive control for robot manipulators under ellipsoidal task space constraints. IEEE International Conference on Intelligent Robots and Systems : 1167-1172. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/IROS.2012.6386257" target="_blank">https://doi.org/10.1109/IROS.2012.6386257</a>
dc.identifier.isbn9781467317375
dc.identifier.issn21530858
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/83438
dc.description.abstractMotivated by applications in robot-assisted physical rehabilitation, this paper presents an adaptive control design for robot manipulators operating in an ellipsoidal constrained region. The ellipsoidal constraint problem is more challenging than the box constraint problem tackled in previous works, since the nonlinear constraint boundary cannot be handled in a decoupled manner along the dimensions of the task space. We introduce a novel Barrier Lyapunov Function (BLF) which contains a quotient of the squared norm of the tracking error over the ellipsoidal task space constraint. This function allows the task space constraint to be handled directly without requiring an intermediate mapping to the error space. We show that, under the proposed BLF-based adaptive control, the end-effector always remains in the constrained region despite the perturbing effects of online parameter adaptation and also the presence of bounded external disturbances. A simulation example illustrates the performance of the proposed control. © 2012 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/IROS.2012.6386257
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/IROS.2012.6386257
dc.description.sourcetitleIEEE International Conference on Intelligent Robots and Systems
dc.description.page1167-1172
dc.description.coden85RBA
dc.identifier.isiutNOT_IN_WOS
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