Autonomous Decentralized Control for Motion Switching in an Intestine-Inspired Peristaltic Mixing Pump Adaptive to Physical Phase Transitions of Mixed Materials

In this paper, we developed an autonomous decentralized control method that incorporates phase-difference adjustment based on a sigmoid function, enabling the design of both increases and decreases in discrepancy. The method was applied to a peristaltic mixing pump capable of mixing and transporting solid–liquid multiphase fluids. This study aims to realize a soft robotics system that autonomously switches motion modes according to changes in the physical properties of the transported material, thereby integratively mimicking both the motility and motion-switching functions of the intestine. Conventional autonomous decentralized control methods have been applied to the locomotion of amoeba-type and snake-type robots. However, when such control laws are applied to pumps, it is difficult to achieve appropriate motion switching in environments where the contents harden due to mixing. In this paper, we employed a sigmoid function that allows bidirectional control of discrepancy and constructed a new control law based on target phase-difference adjustment without feedback. The control law was implemented in a four-unit pump, and we confirmed that the desired motion patterns could be reproduced according to the preset target phase differences. As a result, the phase differences between all units converged to the target values within approximately 10–30 s after actuation began, producing the intended motion patterns. Furthermore, polyvinyl alcohol solution and borax water were used as contents whose fluidity decreases during mixing. We verified that autonomous motion switching occurred as the discrepancy increased. The results showed that, in units containing hardened material, a conveying motion with a phase difference of π/3 was generated, whereas in units with residual unmixed material, a mixing motion with a phase difference of π was generated. These findings demonstrate that the proposed method enables motion control that adapts to changes in material properties.