Modeling and identification of rate-dependent and asymmetric hysteresis of soft bending pneumatic actuator based on evolutionary firefly algorithm

Soft-bending pneumatic actuators (SBPA) have shown great potential in various applications owing to their intrinsic compliance. However, motion control is still challenging because of the complicated hysteresis of the elastic material and pneumatic system, which unlike the general hysteresis found in the rigid body mechanism, is rate-dependent and asymmetric. A precise hysteresis model is crucial for improving the performance of SBPA. This study proposed a rate-dependent modified generalized Prandtl–Ishlinskii (RMGPI) model for a vulcanized silicone rubber-based fast pneu-net soft bending pneumatic actuator (fp-SBPA) to describe complicated hysteresis characteristics. A visual feedback system obtained the bending angle in real time. With the increase in the number of operators, the identification of the proposed model parameters became more complicated and time-consuming; thus, an evolutionary firefly algorithm (EFA) was developed to improve identification efficiency. A series of experiments and comparison studies were conducted to verify the effectiveness of the proposed model and identification method.