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

Feedforward control Gradient based optimization Hysteresis Interval type-2 fuzzy system Piezoelectric actuator

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
02 May 2020
Historique:
received: 24 03 2020
revised: 22 04 2020
accepted: 29 04 2020
entrez: 7 5 2020
pubmed: 7 5 2020
medline: 7 5 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 32370109
pii: s20092587
doi: 10.3390/s20092587
pmc: PMC7249067
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

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Auteurs

Peng-Zhi Li (PZ)

Robotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.

De-Fu Zhang (DF)

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Jun-Yan Hu (JY)

Robotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.

Barry Lennox (B)

Robotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.

Farshad Arvin (F)

Robotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.

Classifications MeSH