High performance periodical paths tracking of two-dimensional handheld micromanipulator using explicit model predictive control

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dc.contributor.authorBoksuwan, Sungwan
dc.contributor.authorCheypoca, Thepjit
dc.contributor.authorChesof, Abdulhafiz
dc.contributor.authorKanamori, Chisato
dc.contributor.authorPanaudomsup, Sumit
dc.contributor.authorSiritechavong, Techin
dc.contributor.authorAoyama, Hisayuki
dc.contributor.authorAnuntahirunrat, Kongsak
dc.date.accessioned2026-08-06T10:16:10Z
dc.date.available2026-08-06T10:16:10Z
dc.date.issued2017-02-18
dc.description.abstractThe paper proposes an explicit model predictive control framework for a two-dimensional handheld micromanipulator to track periodical reference paths within microscopic working range and for all holding angles of users' hand. The control objective is to achieve a minimum tracking error and a wide bandwidth. The micromanipulator's design is oriented to such bio cell treatments. Its structure consists of two flexible decoupling links, each of which is driven by the combination of electric coils and permanent magnets as an actuator. In the experiments, the proposed framework is compared with two types of PID controllers, parameters of which are designed by Skogestand's IMC and IMC method based on the underdamped transfer function, respectively. The experimental results exhibit the effectiveness of the two-dimensional handheld micromanipulator controlled by the model predictive control framework over the PID controller ones.
dc.identifier.citationACM International Conference Proceeding Series, Part F127852, 274-278, 2017
dc.identifier.doi10.1145/3057039.3057107
dc.identifier.other2-s2.0-85020920722
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/7505
dc.sourceACM International Conference Proceeding Series
dc.subjectExplicit model predictive control
dc.subjectHandheld micromanipulator
dc.subjectMicro-scale tracking
dc.subjectPID controller
dc.titleHigh performance periodical paths tracking of two-dimensional handheld micromanipulator using explicit model predictive control
dc.typeConference Paper

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