Observer‐based adaptive emotional command‐filtered backstepping for cooperative control of input‐saturated uncertain strict‐feedback multi‐agent systems

Abstract This paper introduces a distributed observer‐based emotional command‐filtered backstepping (DOECFB) approach for leader‐following cooperative output‐feedback control of heterogenous strict‐feedback multi‐agent systems (MAS) under mismatched uncertainties and input saturation. A novel state observer is designed based on radial‐basis neural networks (RBENNs) that approximate model dynamics. To inter‐agent dynamics with less complexity, emotion‐inspired approximated are shared among neighbouring followers, like contagion in group people. An auxiliary system also used to attenuate saturation's negative effect the tracking performance. Also, command filters compensating signals applied avoid ‘explosion complexity’ design. Only local information from other agents required proposed guarantee convergence error small region around zero cooperatively semi‐globally uniformly ultimately boundedness closed‐loop signals. Simulation examples second‐order uncertain MAS multiple forced‐damped pendulums conducted, quantitative comparisons verify effectiveness DOECFB observer.