Adaptive Fuzzy Sliding Mode Control for Collaborative Robot Based on Nominal Model

Abstract

The seven-degree-of-freedom (7dof) collaborative robot is a type of nonlinear system with multiple inputs, multiple outputs, parameter uncertainties, external disturbances and unmodeled dynamics. Due to the external disturbances, such as friction, uncertainty information and parameters will be generated in the system, which can affect the operation of the robotic arm. Sliding mode control has the advantages of being insensitive to changes in external disturbances and internal disturbances. Based on this, this paper designed a model-based adaptive fuzzy sliding mode controller. On the basis of compensating the unmodeled characteristics of the system, the controller can be deduced by adaptively estimating the uncertainty upper bound, which can eliminate the chattering problem of the control law well. Through the simulation of the seven-degree-of-freedom cooperative robot, it is known that this scheme has higher tracking accuracy than ordinary sliding mode control schemes. Furthermore, it greatly improves the robustness to external interference, system uncertain information and parameter changes.