Rate-Dependent Hysteresis Model of a Giant Magnetostrictive Actuator Based on an Improved Cuckoo Algorithm

Author:

Liu Yang1,Meng Jianjun1234,Cao Jingnian1

Affiliation:

1. School of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

2. Mechatronics T&R Institute, Lanzhou Jiaotong University, Lanzhou 730070, China

3. Engineering and Technology Research Center of Logistics and Transportation Equipment Information of Gansu Province, Lanzhou 730000, China

4. Gansu Logistics and Transportation Equipment Industry Technology Center, Lanzhou 730000, China

Abstract

A rate-dependent asymmetric Prandtl–Ishilinskii (RAPI) model was proposed to tackle the serious rate-dependent hysteresis nonlinearity of the giant magnetostrictive actuator(GMA) output. First, a polynomial function was introduced based on the PI model, and hysteresis factors were introduced to the Play operator, which accurately described the asymmetrical characteristic of the actuator output. On this basis, rate-dependent parameters were added to establish a rate-dependent RAPI model. Second, an improved cuckoo search (ICS) algorithm was proposed to solve the difficulty in the parameter identification of the RAPI model. For the ICS algorithm, the algorithm stability and optimization accuracy were improved using the adaptive step (AS) strategy and bird’s nest disturbance strategy. Then, the effectiveness of the ICS algorithm was tested by comparing it with other parameter identification algorithms. Finally, the rate-dependent RAPI model was verified by combining the output data of the giant magnetostrictive actuator under different frequencies. The results show that the rate-dependent RAPI model exhibits a higher accuracy than the PI model, thus verifying the effectiveness of the rate-dependent RAPI model.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Control and Optimization,Control and Systems Engineering

Reference25 articles.

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5. Derivation and Modification of Analytical Forward Preisach Hysteresis Model;Liu;Proc. CSEE,2023

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