Fully Distributed Anti-Windup Consensus Protocols for Linear MASs With Input Saturation: The Case With Directed Topology. Academic Article uri icon


  • We aim to solve the consensus problem of linear multiagent systems (MASs) with input saturation under directed interaction graphs in this article, where only local output information of neighbors is available for each agent. By introducing the multilevel saturation feedback control approach, a fully distributed adaptive anti-windup protocol is proposed, where a local observer, a distributed observer, as well as an anti-windup observer are separately constructed for each agent to estimate consensus error, achieve consensus for a certain internal state, and provide anti-windup compensator, respectively. A dual protocol is further presented with the distributed observer designed based on the input matrix, which gives a thorough view on the connection between the distributed observer and the anti-windup observer, and provides the opportunity to reduce the order of the controller by designing the integrated distributed anti-windup observer. Then, three types of distributed anti-windup protocols are proposed based on the integrated distributed anti-windup observer, which requires different assumptions. Specifically, the first protocol needs two-hop relay information to generate the local observer to estimate consensus error; the second protocol designs the local observer with absolute output information to estimate the state instead; while the last protocol introduces certain assumption on transmission zero of agents' dynamics to design the unknown input observer to estimate consensus error. All of the protocols are validated by strictly theoretical proof, and are illustrated by performing simulation examples.

published proceedings

  • IEEE Trans Cybern

author list (cited authors)

  • Lv, Y., Fu, J., Wen, G., Huang, T., & Yu, X.

citation count

  • 26

complete list of authors

  • Lv, Yuezu||Fu, Junjie||Wen, Guanghui||Huang, Tingwen||Yu, Xinghuo

publication date

  • May 2021