A new coefficient-adaptive orthonormal basis function model structure for identifying a class of pneumatic soft actuators

Abstract

The class of Pneumatically-driven Lower-pressure Soft Actuators (PLSA) is a popular research topic as it can be potentially used in the surgical robotic applications. One fundamental problem lying in the PLSA research is the lack of a generally validated model for the complex nonlinear dynamic behaviours. In this paper, a new coefficient-adaptive orthonormal basis function model structure is specifically developed for the identification of the general PLSAs. It is a parameter-independent way directly used to identify the dynamic relation between the actuating pressures and the principal degrees of freedom of a PLSA, the bending and the steering. The approach is based on a modified auxiliary kinematic setting. Following the discussion of the identification procedure, the implementations for the double chamber bending and steering are demonstrated. The results show that the proposed approach can accurately capture the nonlinear pressure-shape dynamics. The approach is also efficient in the real-time applications. It can be further used to improve the current control design for the PLSAs in robotic applications.