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Arturo Zavala-Río

dblp:54/682 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › constrained control
bounded input control
0.112007
A Natural Saturating Extension of the PD-With-Desired-Gravity-Compensation Control Law for Robot Manipulators With Bounded Inputs · IEEE Trans. Robotics 2007
Robotics › Motion planning and robot control
manipulator control
0.112007
A Natural Saturating Extension of the PD-With-Desired-Gravity-Compensation Control Law for Robot Manipulators With Bounded Inputs · IEEE Trans. Robotics 2007
Robotics › Motion planning and robot control › manipulator control
PD control with gravity compensation
0.112007
A Natural Saturating Extension of the PD-With-Desired-Gravity-Compensation Control Law for Robot Manipulators With Bounded Inputs · IEEE Trans. Robotics 2007

Methods — techniques the papers use, named apart from their topics

energy shaping · 0.1damping injection · 0.1
YearPublicationVenuePosition
2023 Continuous finite-time fuzzy control of mechanical systems via non-Lipschitz membership functions
Jorge Villalobos-Chin, Andres Pizarro-Lerma, Víctor Santibáñez, Ramón García-Hernández, Arturo Zavala-Río
Eng. Appl. Artif. Intell.5
2007 A Natural Saturating Extension of the PD-With-Desired-Gravity-Compensation Control Law for Robot Manipulators With Bounded Inputs
abstract
This paper proposes a natural saturating extension of the proportional-derivative (PD) with desired gravity compensation (PDdgc) control law for the global regulation of robot manipulators with bounded inputs. Compared with other algorithms previously proposed under the same analytical framework, it proves to be advantageous in several senses. First, it involves a single saturation function at each joint. Second, it does not need to discriminate the terms that shall be bounded, since these are simply all of them included within the only saturation involved at every joint. Experimental results show the effectiveness of the proposed scheme. As far as the authors are aware, no such type of natural saturating extension (i.e., involving only one saturation function at each joint, where all the terms of the controller are embedded) to the bounded input case had been previously proposed for the PDdgc scheme. Furthermore, it is shown how the proposed approach may be conceived within the framework of the energy shaping plus damping injection methodology.
Arturo Zavala-Río, Víctor Santibáñez
IEEE Trans. Robotics1