Bending control of a 3D printed polyelectrolyte soft actuator with uncertain model

Introduction of 3-dimensional (3D) printing in fabrication and increasing applications of intriguing products in soft robotics have led to studies on controllable 3D printed soft actuators. Therefore, a demand for a precise and computationally efficient model for bending control of the 3D printed soft actuators has arisen. This study initially used a grey box strategy for dynamic modeling of a 3D printed soft actuator which undergoes large bending deformations. Yet, the primary model estimated results deviated from experimental results due to uncertainties such as hysteresis and time varying characteristics of the soft actuator in presence of electric field. Thus, a robust feedback control needed for more accurate bending control of the 3D printed polyelectrolyte actuator. In this paper a sliding mode control scheme is developed with the incorporation of Takagi–Sugeno (T-S) fuzzy modeling of a class of complex 3D printed soft actuator system. A set of extreme fuzzy subsystems are derived for modeling purpose of the actuator; then, a sliding mode control law is employed to ensure the stability of the closed-loop fuzzy system and deal with model uncertainties. Finally, the proposed approach is verified by experimental results.