Hybrid gray and black-box nonlinear system identification of an elastomer joint flexible robotic manipulator

Abstract

Series elastic actuators possess several properties that make them widely used in collaborative robots, which play a major role in the current paradigm of industry 4.0. However, the compliant element responsible for those desired properties can also be responsible for the addition of unmodeled nonlinearities in the system. Therefore, the aim of this paper is to propose a novel hybrid model approach and apply it in the modeling of an elastomer-based series elastic joint. The proposed hybrid model combines a phenomenological gray-box model with a black-box Nonlinear Auto-regressive model with Exogenous inputs, which is able to provide the desired physical insight while enhancing accuracy by addressing the unknown nonlinearities. The results showed that the proposed hybrid model is more than 60% more accurate than the phenomenological model, considering the mean square error, and obtained a multiple correlation coefficient up to 0.97, indicating its capacity to be used in the construction of a digital twin of the system.