On the Robust Quantized Sampled–Data Leaderless Consensus Tracking of Nonlinear Multi–Agent Systems
Mario Di Ferdinando, Domenico Bianchi, S. Di Gennaro, Pierdomenico Pepe · 2021 60th IEEE Conference on Decision and Control (CDC) · 2021
This paper deals with the robust quantized sampled–data leaderless consensus tracking problem for nonlinear multi-agent systems (MASs), affected by actuation disturbances and observation errors, over strongly connected networks. The input-to-state stability redesign methodology is used in order to design a new quantized sampled–data control term able to arbitrarily attenuate the effects of bounded actuation disturbances and bounded observation errors. The quantization of both input/output channels is simultaneously considered. It is proved that, by suitably fast sampling and accurately quantizing the continuous–time protocol at hand, the leaderless consensus tracking is ensured, regardless of the above disturbances and errors provided that: (i) the bounds of the actuation disturbances and of the observation errors are a– priori known; (ii) the observation errors do not affect or affect marginally the new added control term. Possible discontinuities in the function describing the protocol are also managed. The cases of time–varying sampling intervals and of non–uniform quantization in the input/output channels are included in the theory here developed. Furthermore, the stability analysis of the inter-sampling system behaviour is performed. The stabilization in the sample-and-hold sense theory is used as a tool for proving the results. The provided results are validated through an application concerning the formation control problem of unmanned aerial vehicles.