Adaptive control of a shape memory alloy actuator using neural-network feedforward and RISE feedback

  • Asad Ullah Awan
  • Jaemann Park
  • Hyoun Jin Kim
  • Junghyun Ryu
  • Maenghyo Cho
Article

Abstract

A This paper presents a position tracking control system for a shape memory alloy (SMA) actuator using neural network (NN) feedforward and robust integral of signum of error (RISE) feedback. Nonlinear control of SMA actuators is difficult due to model uncertainties and unknown disturbances. Discontinuous control techniques such as sliding mode control have conventionally been used to achieve asymptotic tracking in the presence of model uncertainties. However, such discontinuous controllers usually result in increased power loss due to high frequency switching. With the recent development of the continuous RISE feedback control, semi-global asymptotic tracking can be achieved. Furthermore, the NN-RISE control leads to better tracking performance and lower power losses caused by input signal switching/chattering when compared to discontinuous controllers. In order to apply the NN-RISE, a state-space model of the SMA actuator is derived, which has been overlooked in many previous works, using Taylor series expansion and exploiting the nature of SMA dynamics. Experimental results show that the proposed control system works well even in the absence of an accurate model of the SMA actuator.

Keywords

Hysteresis Neural networks Nonlinear adaptive control RISE feedback Shape memory alloy (SMA) actuator 

Nomenclature

h, h0, h1

heat transfer co-efficient parameters

Tamb

ambient temperature, in degrees Celsius

T

SMA wire temperature

I

input current

Rm

martensite fraction

ε

strain

εo

initial strain in SMA wire

σ

stress

Δ

disturbance term

ΔT

lumped uncertainty term in heat-transfer equation

xd, xd(i)

desired trajectory, ith time derivative (resp.)

a11, a12, a21, a22, b1, d1, d2

Taylor series expansion parameters

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Copyright information

© Korean Society for Precision Engineering and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Asad Ullah Awan
    • 1
  • Jaemann Park
    • 2
  • Hyoun Jin Kim
    • 2
  • Junghyun Ryu
    • 2
  • Maenghyo Cho
    • 2
  1. 1.Department of Mechatronics EngineeringNational University of Sciences and TechnologyIslamabadPakistan
  2. 2.School of Mechanical and Aerospace Engineering, Institute of Advanced Aerospace TechnologySeoul National UniversitySeoulSouth Korea

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