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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. [ABSTRACT FROM AUTHOR]

Liquid crystal elastomer is a type of soft material with unique physical and chemical properties that offer a variety of possibilities in the growing field of soft robot actuators. This type of material is able to exhibit large, revertible deformation under various external stimuli, including heat, electric or magnetic fields, light, etc., which may lead to a wide range of different applications such as bio-sensors, artificial muscles, optical devices, solar cell plants, etc. With these possibilities, it is important to establish modeling and control strategies for liquid crystal elastomer-based actuators, to obtain the accurate prediction and description of its physical dynamics. However, so far, existing studies on this type of the actuators mainly focus on material properties and fabrication, the state of art on the modeling and control of such actuators is still preliminary. To gain a better understanding on current studies of the topic from the control perspective, this review provides a brief collection on recent studies on the modeling and control of the liquid crystal elastomer-based soft robot actuator. The review will introduce the deformation mechanism of the actuator, as well as basic concepts. Existing studies on the modeling and control for the liquid crystal elastomer-based actuator will be organized and introduced to provide an overview in this field as well as future insights. [ABSTRACT FROM AUTHOR]

This article proposes a dynamic model and a tracking control strategy for a dielectric elastomer (DE) actuator based on the model predictive controller (MPC). First, the dynamic model of the DE actuator is established, which can describe its asymmetric hysteresis, creep, and even rate-dependent hysteresis behaviors simultaneously. Then, on the basis of the established dynamic model, an inverse compensation controller (ICC) is designed to compensate the hysteresis and creep nonlinearities of the DE actuator on its tracking control. Moreover, the MPC is designed to cooperate with the ICC, which can overcome the influences of the modeling error and uncertainties on the control precision. Finally, several experiments demonstrate the effectiveness of the proposed dynamic model and control strategy. [ABSTRACT FROM AUTHOR]

This paper proposes the modelling and compound control methods for the intelligently dielectric elastomer actuator (IDEA) to realize its dynamic modelling and tracking control objectives. Firstly, we establish a dynamic model of the IDEA by cascading a square input module, a hysteresis model and a linear system, which can simultaneously characterize its asymmetrical and rate-dependent hysteresis behaviours, creep behaviour, as well as vibration behaviour. Then, by cascading the inverse solutions of the hysteresis model and the linear system, as well as the square root function module, an inverse compensation feedforward controller (ICFC) is designed to compensate the aforementioned behaviours of the IDEA in the tracking control. Moreover, considering that the uncertainties of the real system (including the modelling error, model parameter perturbation and external disturbance, etc.) are inescapable, a fuzzy proportional–integral feedback controller is designed to combine with the ICFC to enhance the tracking control performance, whose parameters are automatically adjusted by the fuzzy system. Finally, 6 groups of tracking control experiments with different target trajectories are performed. The maximum value of the relative root-mean-square errors of all experimental results is less than 3.1%, which demonstrates the effectiveness of the proposed compound control method of the IDEA. • Build dynamic model of dielectric elastomer actuator. • Use nonlinear least squares algorithm to identify model parameters with constraints. • Achieve high precision motion control of dielectric elastomer actuator. • Use inverse compensation feedforward controller to compensate nonlinearities. • Use fuzzy PI controller to mitigate modelling errors and disturbances. [ABSTRACT FROM AUTHOR]