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Peng-Zhi Li
Robotics for Extreme Environments Lab, Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK

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Journal article
Published: 02 May 2020 in Sensors
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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.

ACS Style

Peng-Zhi Li; De-Fu Zhang; Jun-Yan Hu; Barry Lennox; Farshad Arvin. Hysteresis Modelling and Feedforward Control of Piezoelectric Actuator Based on Simplified Interval Type-2 Fuzzy System. Sensors 2020, 20, 2587 .

AMA Style

Peng-Zhi Li, De-Fu Zhang, Jun-Yan Hu, Barry Lennox, Farshad Arvin. Hysteresis Modelling and Feedforward Control of Piezoelectric Actuator Based on Simplified Interval Type-2 Fuzzy System. Sensors. 2020; 20 (9):2587.

Chicago/Turabian Style

Peng-Zhi Li; De-Fu Zhang; Jun-Yan Hu; Barry Lennox; Farshad Arvin. 2020. "Hysteresis Modelling and Feedforward Control of Piezoelectric Actuator Based on Simplified Interval Type-2 Fuzzy System." Sensors 20, no. 9: 2587.