Literature DB >> 33501098

Two-Stage Shape Memory Alloy Identification Based on the Hammerstein-Wiener Model.

Dorin Copaci1, Luis Moreno1, Dolores Blanco1.   

Abstract

Thanks to characteristics, such as high force and light weight, a good biocompatibility, noiseless operation and simplicity, and relatively low-cost compared with other conventional actuators, actuators based on shape memory alloy are currently one of the most interesting research topics. They have been introduced in applications such robotics, medicine, automation, and so on. For a good actuator integration of these types of applications, proper control is needed, which seems to be a difficult task due to the hysteresis, dilatory response, and non-linear behavior. This work presents a new form of modeling of this type of actuator based on Hammerstein-Wiener model. This has been identified in two stages of the operation. When the activation temperature for the actuator is obtained by the Joule effect, electrically energy is transformed into thermal energy. In the second stage, the thermal energy is transformed into mechanical work. To fulfill this objective, experimental data [e.g., the input signal (pulse-width modulation), temperature signal, and position signal] from the two stages was obtained for a specific shape memory alloy wire and for specific environmental conditions. This data was used in the modeling process. The final model consists of a combination of the models from the two stages, which represent the behavior of the shape memory alloy actuator where the input signal is the pulse-width modulation signal and the output signal are the position of the actuator. Our results indicate that our model has a very similar response to the behavior of the real actuator. This model can be used to tune different control algorithms, simulate the entry system before manufacture and test on real devices.
Copyright © 2019 Copaci, Moreno and Blanco.

Entities:  

Keywords:  Hammerstein–Wiener; actuator; control; modeling; shape memory alloy

Year:  2019        PMID: 33501098      PMCID: PMC7805934          DOI: 10.3389/frobt.2019.00083

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  4 in total

1.  Investigation of the Hammerstein hypothesis in the modeling of electrically stimulated muscle.

Authors:  K J Hunt; M Munih; N N Donaldson; F M Barr
Journal:  IEEE Trans Biomed Eng       Date:  1998-08       Impact factor: 4.538

2.  The identification of nonlinear biological systems: Wiener and Hammerstein cascade models.

Authors:  I W Hunter; M J Korenberg
Journal:  Biol Cybern       Date:  1986       Impact factor: 2.086

3.  Identification of a Modified Wiener-Hammerstein System and Its Application in Electrically Stimulated Paralyzed Skeletal Muscle Modeling.

Authors:  Er-Wei Bai; Zhijun Cai; Shauna Dudley-Javorosk; Richard K Shields
Journal:  Automatica (Oxf)       Date:  2009-03       Impact factor: 5.944

4.  New Design of a Soft Robotics Wearable Elbow Exoskeleton Based on Shape Memory Alloy Wire Actuators.

Authors:  Dorin Copaci; Enrique Cano; Luis Moreno; Dolores Blanco
Journal:  Appl Bionics Biomech       Date:  2017-09-05       Impact factor: 1.781

  4 in total

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