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A learning control algorithm for periodic robot synchronization: Experimental results
Author(s) -
Gnucci M.,
Gospodarczyk M.,
Carnevale D.,
Tiberti M.,
Tomei P.,
Verrelli C. M.
Publication year - 2018
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2868
Subject(s) - synchronization (alternating current) , tracking (education) , computer science , position (finance) , identifier , control theory (sociology) , robot , task (project management) , joint (building) , control (management) , algorithm , artificial intelligence , engineering , channel (broadcasting) , architectural engineering , psychology , computer network , pedagogy , systems engineering , finance , economics , programming language
Summary A repetitive learning control algorithm, that achieves asymptotic joint position tracking for robotic manipulators characterized by uncertain dynamics and performing a repetitive task, can be theoretically and experimentally endowed with a recursive period identifier. Experimental results illustrate its application to a 2‐link robot master‐slave synchronization problem, in which the joint positions of the master, ie, “periodic” with uncertain and even time‐varying period, are only available at runtime.

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