Dynamic modelling of liquid crystal elastomer actuators based on a physics-phenomenon-combined approach

Abstract

Liquid crystal elastomer-based actuators (LCEAs) exhibit large, reversible deformation, which demonstrates superior advantages in developing remote controlled, light-weighted soft robots. However, deformation of LCEAs undergoes complicated physical dynamics and exhibits highly nonlinear hysteretic characteristics, posing challenges in the realization of related applications. It is necessary to develop a dynamic model that captures the characteristics of LCEAs. With this purpose, this paper proposes a dynamic modelling approach for LCEAs to provide a hybrid model for LCEAs with reduced computational complexity and high precision. In the research, a modelling scheme based on a physics-phenomenon-combined approach for LCEAs is proposed, which considers the elastic free energy, the nematic free energy and dissipation of the LCEA. Physics-based models are then developed to describe these energies. Meanwhile, a phenomenon-based model is proposed to characterise the hysteresis as a component of the nematic free energy. The above models are combined together to provide the final hybrid model for the LCEA. To verify the proposed model, a photo-responsive LCEA experimental platform is established and experiments are conducted. Model parameters are identified based on the nonlinear least-squares method. The experimental results demonstrate the proposed model as an excellent representative to characterise LCEAs' dynamic behaviours.

Keywords:

• Liquid crystal elastomer actuator (LCEA)
• dynamic modelling
• modified Prandtl–Ishlinskii model
• hybrid model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, C.-Y. Su, upon reasonable request.

Additional information

Funding

This paper is supported by the National Natural Science Foundation of China [Grant Nos. 62203407 and 61733006], the China Postdoctoral Science Foundation [Grant Nos. 2022TQ0318 and 2022MT22946] and the ‘CUG Scholar’ Scientific Research Funds at China University of Geosciences [Project No. 2022160 and 2022113].