Observer-Based ILC Applied to the Gantry-Tau Parallel Kinematic Robot: Modelling, Design and Experiments
2010 (English)Report (Other academic)
Three different approaches of iterative learning control (ILC) applied to a parallel kinematic robot are studied. First, the ILC algorithm is based on measured motor angles only. Second, tool-position estimates are used in the ILC algorithm. For evaluation, the ILC algorithm finally is based on measured tool position. Model-based tuning of the ILC filters enables learning above the resonance frequencies of the system. The approaches are compared experimentally on a Gantry-Tau prototype, with the tool performance being evaluated by using external sensors. It is concluded that the tool performance can be improved by using tool-position estimates in the ILC algorithm, compared to when using motor-angle measurements. In the paper applying ILC algorithms to a system following trajectories with so-called lead-in/lead-out is also considered, as well as dynamic modelling of the Gantry-Tau prototype.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. , 21 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2968
Iterative methods, Learning control, Parallel, Robotic manipulators, Estimation algorithms, Performance evaluation
IdentifiersURN: urn:nbn:se:liu:diva-97735ISRN: LiTH-ISY-R-2968OAI: oai:DiVA.org:liu-97735DiVA: diva2:650644