Cooperative Learning-Based Tracking Control of Networked Mobile Robots Under Malicious Packet Losses: Theory and Experiments

Abstract

This article focuses on the cooperative tracking problem for a group of mobile robots (MRs) under modeling uncertainties, malicious packet losses (MPLs), and network-induced delays. First, to cope with MPLs on communications, a data packet analyzer is developed such that the intermittent packet arrival instants under MPLs can be well detected and recorded. Then, a cooperative learning (CL)-based tracking control scheme containing three control layers is designed for the group of MRs to achieve cooperative tracking. Specifically, at the kinematic layer, two networked cooperative tracking guidance laws are developed to coordinate MRs’ movements and prescribe commanded guidance signals of velocities. At the learning layer, by virtue of the designed online CL laws, modeling uncertainties are approximated in a cooperative manner. At the kinetic layer, two resilient dynamic control laws are constructed to regulate the action of involved MRs. It is demonstrated that, under the designed control scheme, the resulting cooperative tracking error dynamics is uniformly ultimately bounded. Finally, simulation and experiment examples are elaborated to verify the effectiveness and merits of the designed control scheme.