Active disturbance rejection control of a parallel manipulator with self learning algorithm for a pulsating trajectory tracking task

A novel and robust intelligent scheme is proposed to control a highly non-linear 3-rrr(revolute-revolute-revolute) planar parallel robotic manipulator, via an active force control (afc)strategy that is embedded into the classic proportional-integral-derivative (pid) control loop. a pid-typeiterative learning (il) algorithm, with randomized initial conditions, is incorporated into the afc loopto approximate the estimated inertia matrices of the manipulator adaptively while the manipulator istracking a prescribed pulsating trajectory in the presence of harmonic disturbances. the il algorithmemploys a stopping criterion, which is based on tracking error, to stop the learning process when thedesired error goal of the system is reached, to signify a favorable controlled condition. a numericalsimulation study was performed to verify the robustness of the proposed methodology in rejectingdisturbances, based on given loading and operating environments. the results of the study reveal thesuperiority of the proposed system, in terms of its excellent tracking performance compared to the afc,with crude approximation techniques, and proportional-integral-derivative (pid) counterparts.