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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1723

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contributor.authorSubudhi, B D-
contributor.authorPradhan, Santanu Kumar-
date.accessioned2012-07-05T12:12:59Z-
date.available2012-07-05T12:12:59Z-
date.issued2010-12-
identifier.citationproceedings of the National System Conference (NSC), 2010, NIT Suratkal, Mangalore, 10-12 Dec. 2010en
identifier.urihttp://hdl.handle.net/2080/1723-
descriptionCopyright belongs to proceeding publisheren
description.abstractIn this paper a new nonlinear adaptive controller using actor-critic based Reinforcement Learning (RL) is proposed to adapt the load pick-up and release operation while following a desired trajectory by the end effector for a Two- Link Flexible Manipulator (TLFM). Simulation results show that the proposed RL based adaptive control gives better trajectory tracking performance and suppression of link vibration compared to conventional adaptive controllers with time varying payload.en
format.extent438309 bytes-
format.mimetypeapplication/pdf-
language.isoen-
subjectFlexible Manipulatoren
subjectReinforcement Learning adaptive controlen
subjectTime varying payloaden
titleReinforcement Learning Based Adaptive Control of a Flexible Manipulatoren
typeArticleen
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