Consensus in High-Power Multiagent Systems With Mixed Unknown Control Directions via Hybrid Nussbaum-Based Control

Maolong Lv, Wenwu Yu, Jinde Cao, Simone Baldi

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

This work investigates the consensus tracking problem for high-power nonlinear multiagent systems with partially unknown control directions. The main challenge of considering such dynamics lies in the fact that their linearized dynamics contain uncontrollable modes, making the standard backstepping technique fail; also, the presence of mixed unknown control directions (some being known and some being unknown) requires a piecewise Nussbaum function that exploits the a priori knowledge of the known control directions. The piecewise Nussbaum function technique leaves some open problems, such as Can the technique handle multiagent dynamics beyond the standard backstepping procedure? and Can the technique handle more than one control direction for each agent? In this work, we propose a hybrid Nussbaum technique that can handle uncertain agents with high-power dynamics where the backstepping procedure fails, with nonsmooth behaviors (switching and quantization), and with multiple unknown control directions for each agent.

Original languageEnglish
Number of pages13
JournalIEEE Transactions on Cybernetics
DOIs
Publication statusAccepted/In press - 1 Jan 2020

Keywords

  • Backstepping
  • Consensus tracking
  • Directed graphs
  • input quantization
  • Multi-agent systems
  • multiagent systems
  • Quantization (signal)
  • switched dynamics
  • Switches
  • Topology
  • unknown control directions

Fingerprint Dive into the research topics of 'Consensus in High-Power Multiagent Systems With Mixed Unknown Control Directions via Hybrid Nussbaum-Based Control'. Together they form a unique fingerprint.

Cite this