MATEC Web Conf.
Volume 145, 2018NCTAM 2017 – 13th National Congress on Theoretical and Applied Mechanics
|Number of page(s)||7|
|Published online||09 January 2018|
Efficient control of mechatronic systems in dynamic motion tasks
Institute of Mechanics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl.4, BG-1113 Sofia, Bulgaria
* Corresponding author: email@example.com
Robots and powered exoskeletons have often complex and non-linear dynamics due to friction, elasticity, and changing load. The proposed study addresses various-type robots that have to perform dynamic point-to-point motion tasks (PTPMT). The performance demands are for faster motion, higher positioning accuracy, and lower energy consumption. With given motion task, it is of primary importance to study the structure and controllability of the corresponding controlled system. The following natural decentralized controllability condition is assumed: the signs of any control input and the corresponding output (the acceleration) are the same, at least when the control input is at its maximum absolute value. Then we find explicit necessary and sufficient conditions on the control transfer matrix that can guarantee robust controllability in the face of arbitrary, but bounded disturbances. Further on, we propose a generic optimisation approach for control learning synthesis of various type robotic systems in PTPMT. Our procedure for iterative learning control (LC) has the following main steps: (1) choose a set of appropriate test control functions; (2) define the most relevant input-output pairs; and (3) solve shooting equations and perform control parameter optimisation. We will give several examples to explain our controllability and optimisation concepts.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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