Evidence map›Paper›PMID 32370109›Full record

ArticleSensors (Basel, Switzerland)2020

Hysteresis Modelling and Feedforward Control of Piezoelectric Actuator Based on Simplified Interval Type-2 Fuzzy System.

Peng-Zhi Li, De-Fu Zhang, Jun-Yan Hu, Barry Lennox, Farshad Arvin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Peng-Zhi LiRobotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.
De-Fu ZhangChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
Jun-Yan HuRobotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.
Barry LennoxRobotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0003-0905-8324
Farshad ArvinRobotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0001-7950-3193

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The piezoelectric actuator is indispensable for driving the micro-manipulator. In this paper, a simplified interval type-2 (IT2) fuzzy system is proposed for hysteresis modelling and feedforward control of a piezoelectric actuator. The partial derivative of the output of IT2 fuzzy system with respect to the modelling parameters can be analytically computed with the antecedent part of IT2 fuzzy rule specifically designed. In the experiments, gradient based optimization was used to identify the IT2 fuzzy hysteresis model. Results showed that the maximum error of model identification is 0.42% with only 3 developed IT2 fuzzy rules. Moreover, the model validation was conducted to demonstrate the generalization performance of the identified model. Based on the analytic inverse of the developed model, feedforward control experiment for tracking sinusoidal trajectory of 20 Hz was carried out. As a result, the hysteresis effect of the piezoelectric actuator was reduced with the maximum tracking error being 4.6%. Experimental results indicated an improved performance of the proposed IT2 fuzzy system for hysteresis modelling and feedforward control of the piezoelectric actuator.

Indexed as

Feedforward controlGradient based optimizationHysteresisInterval type-2 fuzzy systemPiezoelectric actuator

Identifiers

PMID32370109
PMCPMC7249067

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Registered trials

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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.