A Separation-Based Methodology to Consensus Tracking of Switched High-Order Nonlinear Multiagent Systems

Maolong Lv, Wenwu Yu, Jinde Cao, Simone Baldi

Research output: Contribution to journalArticleScientificpeer-review

80 Citations (Scopus)
24 Downloads (Pure)


This work investigates a reduced-complexity adaptive methodology to consensus tracking for a team of uncertain high-order nonlinear systems with switched (possibly asynchronous) dynamics. It is well known that high-order nonlinear systems are intrinsically challenging as feedback linearization and backstepping methods successfully developed for low-order systems fail to work. Even the adding-one-power-integrator methodology, well explored for the single-agent high-order case, presents some complexity issues and is unsuited for distributed control. At the core of the proposed distributed methodology is a newly proposed definition for separable functions: this definition allows the formulation of a separation-based lemma to handle the high-order terms with reduced complexity in the control design. Complexity is reduced in a twofold sense: the control gain of each virtual control law does not have to be incorporated in the next virtual control law iteratively, thus leading to a simpler expression of the control laws; the power of the virtual and actual control laws increases only proportionally (rather than exponentially) with the order of the systems, dramatically reducing high-gain issues.

Original languageEnglish
Pages (from-to)5467-5479
JournalIEEE Transactions on Neural Networks and Learning Systems
Issue number10
Publication statusPublished - 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Consensus tracking
  • high-order nonlinear systems
  • multiagent systems
  • switching dynamics


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