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Zongpei Wang

dblp:08/1302 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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
1 paper
Motion planning and robot control · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Integrated circuit design · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control
0.012001
New Control Strategy of Variable Reluctance Direct Drive Motor for Robotic Applications · ICRA 2001
Integrated circuit design
electric machine design
0.012001
New Control Strategy of Variable Reluctance Direct Drive Motor for Robotic Applications · ICRA 2001

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

proportional-integral control · 0.1fuzzy control · 0.1PWM control · 0.1
YearPublicationVenuePosition
2001 New Control Strategy of Variable Reluctance Direct Drive Motor for Robotic Applications
abstract
Dual Stator Variable Reluctance Motors (VRM) are electrically commutated ac machines and can be used as direct drive actuators, but inherent nonlinearity of VRM results in difficulties, when smooth and quiet operation are required. In this paper, a high performance control system for VRM is presented. The whole control algorithms consist of four closed-loop controllers: position, velocity, torque and current controller. In the torque controller, the torque ripple is reduced via the torque-sharing function and current PWM control, and the command current is easily obtained from the shared torque command via the proposed nonlinear model of the motor. The velocity controller is a combination of fuzzy and proportional-integral algorithm. The lead angle algorithm is also introduced to improve the performance of system in high speed. The position controller is intended for velocity trajectory tracking. The experimental results illustrate the effectiveness of the control system.
Dianguo Xu 0001, Zongpei Wang
ICRA3