Model predictive control for tracking of repetitive organ motions during teleoperated laparoscopic interventions

Periodic deformations of organs which are due to respiratory movements may be critical disturbances for surgeons manipulating robotic control systems during laparoscopic interventions or tele-surgery. Indeed, the surgeon has to manually compensate for these motions if accurate gestures are needed, like, e.g., during suturing. This paper proposes a repetitive model predictive control scheme for driving a surgical robot towards the reference trajectory defined by the surgeon, while tracking periodic disturbances of known periods on the output. A new cost function is developed for an unconstrained generalized predictive control scheme based on a repetitive multiple input-output model of the robot. Contributions of the controller output to reference tracking and to disturbance rejection are split and computed separately; then, filtering of repetitive disturbances and tracking of the reference trajectory can be independently weighted by the controller while simultaneously running on the plant. The proposed control scheme is validated through simulations and experimental results shown in a surgical robotics application.