A new congruency-based hysteresis modeling and compensating of a piezoactuator incorporating an adaptive neuron fuzzy inference system. (May 2017)

• Record Type: Journal Article
• Authors: Nguyen, Phuong-Bac; Choi, Seung-Bok; Song, Byung-Keun
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 231:Number 9(2017)
• Page Start: 1712
• Page End: 1724
• Publication Date: 2017-05
• Subjects: Congruency-based hysteresis model -- adaptive neuron fuzzy system -- rate-independent hysteresis; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/0954406215620451
• Languages: English
• ISSNs: 0954-4062

Abstract

This paper proposes a new approach to modeling and compensating for a rate-independent hysteresis of a piezoactuator. The model—namely, congruency-based hysteresis—is developed based on two very important characteristics of the hysteresis. These are congruency and wipe-out. The proposed approach consists of two branches for cases of monotonic increase and monotonic decrease of input excitation. In order to realize this model, datasets of first-order minor-loop values should be determined in advance. This can be done using the adaptive neuron fuzzy system (ANFIS) technique and experimental data. With this technique, an input-output relationship of first-order minor-loop values is estimated effectively. In addition, the ANFIS technique is also used in constructing datasets of inverse first-order minor-loop values, which are essential parts of a congruency-based hysteresis compensator. Several experiments in modeling and open-loop control are conducted to show the effectiveness of the proposed approach. In addition, a comparative work between the proposed approach and one of previous works is undertaken to demonstrate the benefit of the proposed method.