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Research Papers

ANFIS Driven Strain Control of Thin-Shape Memory Alloy Wires Using Seebeck Voltage of a Shape Memory Alloy–Constantan Thermocouple

[+] Author and Article Information
V. V. N. Sriram Malladi

Center for Intelligent Material Systems
and Structures,
Department of Mechanical Engineering,
Virginia Polytechnic Institute and State University,
Blacksburg, VI 24061
e-mail: sriram@vt.edu

Pablo A. Tarazaga

Mem. ASME
Center for Intelligent Material Systems
and Structures,
Department of Mechanical Engineering,
Virginia Polytechnic Institute and State University,
Blacksburg, VI 24061
e-mail: ptarazag@vt.edu

Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received March 31, 2014; final manuscript received August 18, 2014; published online November 12, 2014. Assoc. Editor: Eugenio Dragoni.

J. Vib. Acoust 137(1), 011008 (Feb 01, 2015) (11 pages) Paper No: VIB-14-1117; doi: 10.1115/1.4028455 History: Received March 31, 2014; Revised August 18, 2014; Online November 12, 2014

Shape memory alloy (SMA) actuators exhibit considerable hysteresis between the supply voltage (conventionally used in resistive heating) and strain characteristics of the SMA. Hence, it is not easy to control the strain of a thin-SMA wire, unless a model is developed that can match the actuator's nonlinearities for predicting the supply voltage required by the SMA system accurately. The work presented in this paper proposes the use of a black-box technique called the adaptive neurofuzzy inference system (ANFIS) to study the hysteretic behavior of SMAs. The input parameters for such an ANFIS model would be a physical variable at time t and at a time t + n, where n is a time shift. The present work studies the effect of a time shift on the actuator nonlinearities for two ANFIS models. One of the models studies the relationship between the desired displacement of an SMA and the supply voltage across the SMA, while the other model predicts the actual displacement of an SMA from the feedback temperature. A novel SMA–Constantan thermocouple records the feedback temperature.

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References

Figures

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Fig. 1

Layers of an ANFIS model

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Fig. 2

SMA–Constantan thermocouple

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Fig. 3

Schematic showing the different models involved in this system

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Fig. 4

Input MFs of ANFIS Seebeck voltage versus tip temperature

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Fig. 5

Training and validation data of ANFIS Seebeck voltage versus tip temperature

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Fig. 6

Experimental setup to study the strain characteristics of thin SMA wires

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Fig. 7

Time-shifted inputs to ANFIS displacement–voltage model

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Fig. 8

Effect of time-shift on single-loop ANFIS displacement–voltage model

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Fig. 9

Inputs to optimum single-loop ANFIS displacement–voltage model

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Fig. 10

Influence of MFs on single-loop ANFIS displacement versus voltage

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Fig. 11

Variation of RMSE with epochs

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Fig. 12

ANFIS model and experimental voltage signal

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Fig. 13

Voltage–displacement hysteresis curves

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Fig. 14

Time-shifted inputs to ANFIS temperature–displacement model

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Fig. 15

Effect of time-shift on single-loop ANFIS temperature–displacement model

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Fig. 16

Inputs to optimum single-loop ANFIS temperature–displacement model

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Fig. 17

Variation of RMSE with epochs for ANFIS temperature–displacement model

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Fig. 18

Comparison of experimental and ANFIS predicted displacement signal

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Fig. 19

Temperature–displacement hysteresis curves

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Fig. 20

Variation of RMSE time-shift and MFs for a single–loop ANFIS displacement versus voltage model

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Fig. 21

Closed-loop to control SMA system

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Fig. 22

Desired trajectory

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Fig. 23

Inputs for open-loop control

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Fig. 24

Output voltage predicted by displacement–voltage model

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Fig. 25

Open-loop trajectory

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Fig. 26

Closed-loop trajectory

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