Evidence map›Paper›PMID 36422454›Full record

ArticleMicromachines2022

A Convolutional Dynamic-Jerk-Planning Algorithm for Impedance Control of Variable-Stiffness Cable-Driven Manipulators.

Luyang Zhang, Lihui Jia, Panpan Yang, Zixuan Li, Yuhuan Zhang, Xiang Cheng, Zonggao Mu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 48% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Luyang ZhangShandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.
Lihui JiaShandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.
Panpan YangShandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.
Zixuan LiShandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.
Yuhuan ZhangShandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.
Xiang ChengShandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.
Zonggao MuShandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.ORCID 0000-0003-1841-6680
Shandong University of Technology · CN

Funding

the Basic Research Program of Shenzhen JCYJ20190806142818365the China Postdoctoral Science Foundation 2021M702023the National Key Research and Development Project of China 2018YFB2001400the National Natural Science Foundation of China 61903100the Nature Science Foundation of Shandong Province ZR2020ME157the Nature Science Foundation of Shandong Province ZR2021QE183the Nature Science Foundation of Shandong Province ZR2022QE157
6 · The paper itself

Abstract

Cable-driven manipulators, characterized by slender arms, dexterous motion, and controllable stiffness, have great prospects for application to capture on-orbit satellites. However, it is difficult to achieve effective motion planning and stiffness control of cable-driven manipulators because of the coupled relationships between cable lengths, joint angles, and reaction forces. Therefore, a convolutional dynamic-jerk-planning algorithm is devised for impedance control of variable-stiffness cable-driven manipulators. First, a variable-stiffness cable-driven manipulator with universal modules and rotary quick-change modules is designed to overcome difficulties related to disassembly, installation, and maintenance. Second, a convolutional dynamic-jerk-planning algorithm is devised to overcome the discontinuity and shock problems of the manipulator's velocity during intermittent control processes. The algorithm can also make acceleration smooth by setting jerk dynamically, reducing acceleration shock and ensuring the stable movement of the cable-driven manipulator. Third, the stiffness of the cable-driven manipulator is further optimized by compensating for the position and velocity of drive cables by employing position-based impedance control. Finally, the prototype of the variable-stiffness cable-driven manipulator is developed and tested. The convolutional dynamic-jerk-planning algorithm is used to plan the desired velocity curves for velocity control experiments of the cable-driven manipulator. The results verify that the algorithm can improve the acceleration smoothness, thereby making movement smooth and reducing vibrations. Furthermore, stiffness control experiments verify that the cable-driven manipulator has ideal variable stiffness capabilities.

Indexed as

cable-driven manipulatorsimpedance controlmotion controlvariable-stiffness

Identifiers

PMID36422454
PMCPMC9692525
OpenAlexW4309737265

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.