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Wen-Sen Chang

dblp:33/8982 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1988
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

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
2 papers
Motion planning and robot control · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › force control
adaptive force control
0.011988
Dynamic and adaptive force controllers for robotic manipulators · ICRA 1988
Robotics › Motion planning and robot control › robot control
force control
0.011988
Dynamic and adaptive force controllers for robotic manipulators · ICRA 1988
Robotics › Motion planning and robot control › robot control
redundant manipulator control
0.011988
Multivariable self-tuning control of redundant manipulators · IEEE J. Robotics Autom. 1988
Robotics › Motion planning and robot control
robot control
0.011988
Multivariable self-tuning control of redundant manipulators · IEEE J. Robotics Autom. 1988
Robotics › Motion planning and robot control › robot control › adaptive control
self-tuning control
0.011988
Multivariable self-tuning control of redundant manipulators · IEEE J. Robotics Autom. 1988

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

self-tuning control · 0.0recursive least squares · 0.0generalized cost function minimization · 0.0dynamic compensation · 0.0adaptive control · 0.0
YearPublicationVenuePosition
1988 Dynamic and adaptive force controllers for robotic manipulators
abstract
A unified dynamic force control structure is proposed, based on which three force controllers with different dynamics compensations are developed. To deal with the instability problem caused by high environmental stiffness and the robustness problem introduced by model uncertainty, two adaptive force controllers are proposed. Some typical simulation results on a manipulator with three degrees of freedom are presented to test the effectiveness of and to make a performance comparison among these force controllers.>
Mei-Hua Liu, Wen-Sen Chang, Liang-Qi Zhang
ICRA2
1988 Multivariable self-tuning control of redundant manipulators
abstract
An efficient self-tuning control design method for redundant robotic manipulators is presented. With the nominal torques compensating the nonlinear interactions among the joints, the complex nonlinear dynamic equations are linearized and a linear input-output perturbation difference model is developed. Based on which two self-tuning control schemes are proposed in joint and Cartesian spaces. The controller parameters are estimated by the recursive least squares identification algorithm, and the modification torques are generated by minimizing a generalized cost function. Some typical simulation results are presented to demonstrate the effectiveness of these self-tuning control schemes.>
Mei-Hua Liu, Wen-Sen Chang, Liang-Qi Zhang
IEEE J. Robotics Autom.2