Error Convergence Analysis and Stability of a Cloud Control AGV

Shreya Tayade, Peter Rost, Andreas Maeder

In: Workshop on Next Generation Networks and Applications, TU Kaiserslautern. Workshop on Next Generation Networks and Applications (NGNA-2020) December 14-18 Germany TU Kaiserslautern 2020.


In this paper, we present a cloud based Automated Guided vehicle (AGV) control system. A controller in an Edge cloud sends the control inputs to an AGV to follow a predefined reference track over a wireless channel. The AGV feedback the position update via uplink channel. The objective of this paper is to evaluate the stability criterion of an AGV control system in presence of an uplink channel outages. Moreover, we also analyse the impact of feedback control parameters on the error convergence. The results show error convergence at higher rate with optimal selection of feedback parameters. The optimal feedback parameters that converges the error with critical damping is evaluated for two scenarios; with limited AGV velocity and without the limitation on AGV velocity. Furthermore, the paper describe the discretization process of a continuous control AGV system.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence