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

Li, Pengzhi ORCID: 0000-0001-8883-1885, Zhang, De-Fu, Hu, Jun-Yan, Lennox, Barry and Arvin, Farshad (2020) Hysteresis Modelling and Feedforward Control of Piezoelectric Actuator Based on Simplified Interval Type-2 Fuzzy System. Sensors, 20 (9). Art 2587. doi:10.3390/s20092587

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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.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Hysteresis; Piezoelectric actuator; Interval type-2 fuzzy system; Feedforward control; Gradient based optimization
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Pengzhi Li
Date Deposited:	15 Dec 2020 12:46
Last Modified:	13 Mar 2024 13:19
URI:	https://eprints.glos.ac.uk/id/eprint/9079

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