Soft pneumatic actuators adapted in multiple environments: A novel fuzzy cascade strategy for the dynamics control with hysteresis compensation

Abstract

Soft pneumatic actuators (SPAs) have been widely used in the design of various soft robots due to their compliance, adaptability, and high force density characteristics. However, it is a challenge to accurately model and control such soft pneumatic robotic systems due to inherent hysteresis nonlinearity, uncertainties, and disturbances from external environments. In this paper, we propose a novel fuzzy cascade strategy to control the dynamics of bellow-type soft pneumatic actuators when working in multiple environments (air, water, and their transition process). First, the components of the soft pneumatic system including the actuator and solenoid valve are mathematically modeled using second-order transfer functions, which are derived with a system identification method. Then, the Prandtl-Ishlinskii (P-I) model is proposed to accommodate and characterize the complex hysteresis effect. In the P-I model, the parameters are identified and derived using a particle swarm optimization (PSO) method. Subsequently, an inverse P-I model is constructed and placed in the feed-forward path to compensate for the hysteresis effect. In addition to the hysteresis nonlinearity, the uncertainties and disturbances from multiple environments will also degrade the tracking performance of soft pneumatic actuators. To enhance the adaptability, especially during the trans-environment process (e.g., from air into water or the reverse), a single-input FUZZY P+ID controller is proposed and integrated into the cascade strategy aiming to improve the robustness and precisely control the system dynamics. Extensive simulations and real-world tracking experiments of soft pneumatic actuators fabricated with the fused deposition modeling (FDM) method are performed to evaluate the performance of the proposed strategy and three designed controllers (PID, fuzzy PID, and FUZZY P+ID). It is noted that the comparison of tracking results has proved that the proposed FUZZY P+ID controller with only single input has better overall performance than traditional PID and fuzzy PID controllers in terms of adaptability and robustness.