Precision Motion Control of a 6-DoFs Industrial Robot With Accurate Payload Estimation

Along with the traditional motion control demands, human-machine collaboration properties are becoming increasingly important in modern robotic control system. The collaboration requires both robot's dynamics and payload dynamics, in which the former can be identified offline, whereas the latter has to be estimated online. However, the accurate payload estimation cannot be guaranteed by the traditional adaptive control where the adaptation law and the control law are synthesized together to achieve the same goal of reducing tracking errors. To achieve precision motion control and accurate payload estimation simultaneously, this article first developed an identification method for a 6-DoFs industrial robot, which simplifies the excitation trajectory optimization and captures the main dynamics using fewer parameters; and then proposed an integrated direct/indirect adaptive robust control (DIARC) algorithm. Specifically, the proposed DIARC consists of a generalized momentum-based indirect adaptation law to estimate the payload online, a fast direct term to compensate for the adaptation transients, and a robust feedback to attenuate the uncertain nonlinearities. Finally, comparative experiments show that the payload is estimated to the true value and better tracking performances can be achieved by the proposed controller.