Tracking Control of Shape Memory Alloy Flexible Actuators Using Dynamic Surface Controller with Approximate Duhem Model*

As a class of flexible function materials, shape memory alloys (SMAs) can produce the deformation and recovery tension with the change of the phases caused by the temperature difference, fulfilling the conversion of thermal energy and mechanical energy bidirectionally. The flexible actuating characteristics of the SMA have gradually been applied in the fields of bionic robots and aerospace. However, there are strong saturated hysteresis nonlinearities existing between the input-output of the SMA actuators due to the internal materials properties, causing the output accuracy to descend seriously, even instability for some special cases. To overcome the negative effects from the saturated hysteresis, an adaptive dynamic surface controller (ADSC) is proposed in this paper, where the internal hysteresis is modeled by an approximate Duhem model. The designed controller can ensure the output performance of the SMA actuator, and the tracking experiment is conducted to illustrate the effectiveness of the proposed control method.

[1]  Hui Jiang,et al.  Jiles-Atherton Based Hysteresis Identification of Shape Memory Alloy-Actuating Compliant Mechanism via Modified Particle Swarm Optimization Algorithm , 2019, Complex..

[2]  Chenguang Yang,et al.  Physical Human–Robot Interaction of a Robotic Exoskeleton By Admittance Control , 2018, IEEE Transactions on Industrial Electronics.

[3]  Sangyoon Lee,et al.  Design of an shape memory alloy-actuated biomimetic mobile robot with the jumping gait , 2013 .

[4]  Rajnikant V. Patel,et al.  Modeling and Control of Shape Memory Alloy Actuators , 2008, IEEE Transactions on Control Systems Technology.

[5]  Harvey Thomas Banks,et al.  Hysteresis modeling in smart material systems , 1998 .

[6]  Jing Chen,et al.  Parameter identification to an approximated function of the Weierstrass approximation formula , 2012, 2012 24th Chinese Control and Decision Conference (CCDC).

[7]  Luis Moreno,et al.  Position control of a shape memory alloy actuator using a four-term bilinear PID controller , 2015 .

[8]  Xinkai Chen,et al.  Adaptive control for continuous-time systems with actuator and sensor hysteresis , 2016, Autom..

[9]  M. Moallem,et al.  Tracking Control of an Antagonistic Shape Memory Alloy Actuator Pair , 2009, IEEE Transactions on Control Systems Technology.

[10]  Bernard D. Coleman,et al.  On a class of constitutive relations for ferromagnetic hysteresis , 1987 .

[11]  Nguyen Trong Tai,et al.  Output Feedback Direct Adaptive Controller for a SMA Actuator With a Kalman Filter , 2012, IEEE Transactions on Control Systems Technology.

[12]  Ying Feng,et al.  A Modified Prandtl-Ishlinskii Hysteresis Modeling Method with Load-dependent Delay for Characterizing Magnetostrictive Actuated Systems , 2018 .

[13]  Guang-Ren Duan,et al.  Robust adaptive dynamic surface control of uncertain nonlinear systems , 2011 .

[14]  Gangbing Song,et al.  Compensation of hysteresis in a shape memory alloy wire system using linear parameter-varying gain scheduling control , 2014 .