Active Disturbance Rejection Terminal Sliding Mode Control for Tele-Aiming Robot System Using Multiple-Model Kalman Observers

This study proposes a tele-aiming control strategy for the ground reconnaissance robot to track maneuvering target rapidly in presence of dynamic uncertainties, sensory measurement noises, and time-varying external disturbances. First, trajectory generated by human–computer interaction (HCI) device is filtered with tracking differentiator recursive average filter. Second, inertial impact force disturbance jointly other uncertainties (e.g., internal friction, modeling error, etc.) considered as lumped disturbance, then novel multiple-model augmented-state extended Kalman observer (MEKO) designed, capable filtering out joint noises estimating simultaneously. Lastly, nonsingular terminal sliding mode controller applied eliminate joints corresponding desired trajectory. To verify performance, random experiments are designed simulate targets. As indicated from experimental results, proposed significantly suppressing effect achieving fast stable control.