An intersample predictor control scheme based on multirate GPC for high-speed tracking tasks

While robotics has thrived in ordered domains, it has found challenges in environments that are not well defined. Computer vision can extend the feedback measurement space to include the relative position and orientation of the robot end-effector. The role of computer vision as the feedback transducer strongly affects the closed-loop dynamics of the overall system. Researches on visual servo system have up to date focused mainly on preview control, only a few papers have focused on prediction control. However, all of them have not considered coordinate transformation problem caused from the multirate characteristics of visual servo system while performing a high speed tracking task. In this paper, a novel visual servo prediction control scheme is proposed for achieving high speed tracking and high control accuracy. In view of the long time-delay and coordinate transformation problem caused by high speed motion, the use of an intersample predictor based on multirate generalized predictive control (GPC) is proposed to take care of external uncertainties and compute the optimal intersample control inputs of the robotic system. Finally, simulation and experimental results are given to show the drastic effectiveness of proposed approach.