TY - JOUR

T1 - A sliding mode control using an extended Kalman filter as an observer for stimulus-responsive polymer fibres as actuator

AU - Schimmack, Manuel

AU - Mercorelli, Paolo

PY - 2017

Y1 - 2017

N2 - This paper presents a single-input and single-output (SISO) adaptive sliding mode control (SMC) combined with an extended Kalman filter (EKF), which is used as an observer to control stimulus-responsive polymer fibres as an actuator. Conductive metal-polymer fibres are the fundamental core for wearable technology and an integral part of smart textiles. To control this actuator a SMC is combined with an EKF and used as an observer to estimate the velocity. Despite the particular simplified model of the considered actuator, the EKF presents a nonlinear Jacobian matrix. The parameter settings of the system and measurement covariance matrix, together with their initial values, are done heuristically. Because of the slow velocity of the fibre, the EKF produces poor estimation results. Therefore, a derivative approximation structure is proposed to estimate the velocity though the measurement of the position. Both estimations are analysed based on simulations. The simulation results indicate that the proposed algorithm is effective and robust.

AB - This paper presents a single-input and single-output (SISO) adaptive sliding mode control (SMC) combined with an extended Kalman filter (EKF), which is used as an observer to control stimulus-responsive polymer fibres as an actuator. Conductive metal-polymer fibres are the fundamental core for wearable technology and an integral part of smart textiles. To control this actuator a SMC is combined with an EKF and used as an observer to estimate the velocity. Despite the particular simplified model of the considered actuator, the EKF presents a nonlinear Jacobian matrix. The parameter settings of the system and measurement covariance matrix, together with their initial values, are done heuristically. Because of the slow velocity of the fibre, the EKF produces poor estimation results. Therefore, a derivative approximation structure is proposed to estimate the velocity though the measurement of the position. Both estimations are analysed based on simulations. The simulation results indicate that the proposed algorithm is effective and robust.

KW - EKF

KW - Extended Kalman filter

KW - Lyapunov approach

KW - Nonlinear actuators

KW - Observer

KW - Sliding mode control

KW - SMC

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85016014046&partnerID=8YFLogxK

U2 - 10.1504/IJMIC.2017.082951

DO - 10.1504/IJMIC.2017.082951

M3 - Journal articles

AN - SCOPUS:85016014046

VL - 27

SP - 84

EP - 91

JO - International Journal of Modelling, Identification and Control

JF - International Journal of Modelling, Identification and Control

SN - 1746-6172

IS - 2

ER -